if (!require("dplyr")) install.packages("dplyr")
## Loading required package: dplyr
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
if (!require("skimr")) install.packages("skimr")
## Loading required package: skimr
if (!require("tidyr")) install.packages("tidyr")
## Loading required package: tidyr
if (!require("survival")) install.packages("survival")
## Loading required package: survival
if (!require("survminer")) install.packages("survminer")
## Loading required package: survminer
## Loading required package: ggplot2
## Loading required package: ggpubr
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## Attaching package: 'survminer'
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## 
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if (!require("haven")) install.packages("haven")
## Loading required package: haven
if (!require("broom")) install.packages("broom")
## Loading required package: broom
if (!require("rms")) install.packages("rms")
## Loading required package: rms
## Loading required package: Hmisc
## 
## Attaching package: 'Hmisc'
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##     format.pval, units
if (!require("tidyverse")) install.packages("tidyverse")
## Loading required package: tidyverse
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats   1.0.0     ✔ readr     2.1.5
## ✔ lubridate 1.9.4     ✔ stringr   1.5.1
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if (!require("tableone")) install.packages("tableone")
## Loading required package: tableone
library(dplyr)
library(skimr)
library(tidyr)
library(survival)
library(survminer)
library(haven)
library(broom)
library(rms)
library(tidyverse) 
library(tableone)
NHANES2 <- read.csv("NHANES2-1 (1).csv")
d <- NHANES2 #%>% 
  #select('ROWNAMES','SEX','RACE','MARRY','DEATH','AGEYRS',
                    #'GRADES','WT', 'BOOZE', 'SIZE',
         #'AVGSMK', "HEIGHT", "EXAM_YR", "DIE_YR", "LAST_YR")
#Exclude missing death 
d <- d %>%
  filter(!is.na(BOOZE), !is.na(DEATH), !is.na(SEX), !is.na(RACE), !is.na(GRADES), !is.na(AVGSMK), !is.na(SIZE), !is.na(GRADES))

#BMI
d <- d %>%
  mutate(BMI = WT / (HEIGHT / 100)^2)

head(d$BMI)
## [1] 20.49522 21.02151 23.22748 35.72785 27.92312 30.50132
# GRADES and SIZE categories
d$EDUC_CAT <- cut(d$GRADES,
                  breaks = c(-Inf, 8, 11, 12, 15, Inf),
                  labels = c("≤8 yrs", "Some HS", "HS Grad", "Some College", "College+"),
                  right = TRUE)

d$SIZE_CAT <- cut(d$SIZE,
                  breaks = c(0, 3, 5, 7, 8),
                  labels = c("Rural", "Small town", "Medium city", "Large city"),
                  right = TRUE)

# Catergorical BOOZE
d <- d %>%
  mutate(BOOZE_q = cut(
    BOOZE,
    breaks = c(-1, 0, 0.5, 2.0, 77.0),
    include.lowest = TRUE,
    labels = c("0/week", "0–0.5/week", "0.5–2/week", ">2/week")
  ))

vars <- c("AGEYRS", "SEX", "RACE", "MARRY", "BMI", "AVGSMK", "EDUC_CAT", "SIZE_CAT")
catVars <- c("SEX", "RACE", "MARRY")

#Table 1

table1 <- CreateTableOne(vars = vars, 
                         data = d, 
                         strata = "BOOZE_q",  
                         factorVars = catVars)

print(table1, showAllLevels = TRUE)
##                     Stratified by BOOZE_q
##                      level        0/week        0–0.5/week    0.5–2/week   
##   n                                4053           941          1729        
##   AGEYRS (mean (SD))              57.09 (12.79) 54.34 (13.36) 51.60 (13.53)
##   SEX (%)            1             1448 (35.7)    367 (39.0)    856 (49.5) 
##                      2             2605 (64.3)    574 (61.0)    873 (50.5) 
##   RACE (%)           1             3497 (86.3)    827 (87.9)   1515 (87.6) 
##                      2              475 (11.7)     93 ( 9.9)    194 (11.2) 
##                      3               81 ( 2.0)     21 ( 2.2)     20 ( 1.2) 
##   MARRY (%)          2             2885 (71.2)    683 (72.6)   1288 (74.5) 
##                      3              671 (16.6)    127 (13.5)    172 ( 9.9) 
##                      4              190 ( 4.7)     67 ( 7.1)    102 ( 5.9) 
##                      5               96 ( 2.4)     20 ( 2.1)     59 ( 3.4) 
##                      6              202 ( 5.0)     40 ( 4.3)    103 ( 6.0) 
##                      8                9 ( 0.2)      4 ( 0.4)      5 ( 0.3) 
##   BMI (mean (SD))                 26.55 (5.50)  26.42 (5.10)  26.03 (4.84) 
##   AVGSMK (mean (SD))               4.82 (10.84)  6.72 (12.63)  8.26 (13.77)
##   EDUC_CAT (%)       ≤8 yrs        1452 (35.8)    217 (23.1)    337 (19.5) 
##                      Some HS        753 (18.6)    185 (19.7)    282 (16.3) 
##                      HS Grad       1209 (29.8)    311 (33.0)    636 (36.8) 
##                      Some College   353 ( 8.7)    130 (13.8)    235 (13.6) 
##                      College+       286 ( 7.1)     98 (10.4)    239 (13.8) 
##   SIZE_CAT (%)       Rural         1101 (27.2)    348 (37.0)    758 (43.8) 
##                      Small town     454 (11.2)    123 (13.1)    244 (14.1) 
##                      Medium city    569 (14.0)    118 (12.5)    205 (11.9) 
##                      Large city    1929 (47.6)    352 (37.4)    522 (30.2) 
##                     Stratified by BOOZE_q
##                      >2/week       p      test
##   n                   2527                    
##   AGEYRS (mean (SD)) 51.71 (13.18) <0.001     
##   SEX (%)             1678 (66.4)  <0.001     
##                        849 (33.6)             
##   RACE (%)            2250 (89.0)   0.010     
##                        236 ( 9.3)             
##                         41 ( 1.6)             
##   MARRY (%)           1972 (78.0)  <0.001     
##                        170 ( 6.7)             
##                        168 ( 6.6)             
##                         70 ( 2.8)             
##                        140 ( 5.5)             
##                          7 ( 0.3)             
##   BMI (mean (SD))    25.20 (4.08)  <0.001     
##   AVGSMK (mean (SD))  9.60 (13.92) <0.001     
##   EDUC_CAT (%)         387 (15.3)  <0.001     
##                        354 (14.0)             
##                        876 (34.7)             
##                        411 (16.3)             
##                        499 (19.7)             
##   SIZE_CAT (%)        1239 (49.0)  <0.001     
##                        346 (13.7)             
##                        261 (10.3)             
##                        681 (26.9)
#Create follow-up time
d$start <- d$EXAM_YR + d$EXAM_MO / 12


d$end <- ifelse(d$DEATH == 1,
                      d$DIE_YR + d$DIE_MO / 12,
                      d$LAST_YR + d$LAST_MO / 12)

d$FU <- d$end - d$start

#Check for nonlinearity
##Spline Analysis
cox_nl <- coxph(Surv(FU, DEATH) ~ pspline(BOOZE, df = 4), data = d, ties = 'efron')
termplot(cox_nl, term = 1, se = TRUE,
         xlab = "BOOZE (drinks/week)",
         ylab = "Partial log hazard",
         main = "Nonlinearity Check: BOOZE")

cox_nl1 <- coxph(Surv(FU, DEATH) ~ pspline(BOOZE, df = 4) + SEX + AGEYRS +
               as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
               AVGSMK + as.factor(SIZE_CAT), data = d, ties = 'efron')
summary(cox_nl1)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ pspline(BOOZE, df = 4) + SEX + 
##     AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                           coef      se(coef) se2      Chisq   DF   p       
## pspline(BOOZE, df = 4), l  0.011611 0.004829 0.004455    5.78 1.00  1.6e-02
## pspline(BOOZE, df = 4), n                                6.32 3.05  1.0e-01
## SEX                       -0.616923 0.049658 0.049598  154.34 1.00  1.9e-35
## AGEYRS                     0.095053 0.002773 0.002770 1174.98 1.00 1.7e-257
## as.factor(RACE)2          -0.039245 0.075292 0.075262    0.27 1.00  6.0e-01
## as.factor(RACE)3          -0.323827 0.199131 0.199112    2.64 1.00  1.0e-01
## as.factor(EDUC_CAT)Some H -0.003546 0.062232 0.062225    0.00 1.00  9.5e-01
## as.factor(EDUC_CAT)HS Gra -0.068766 0.057582 0.057555    1.43 1.00  2.3e-01
## as.factor(EDUC_CAT)Some C -0.210260 0.082674 0.082642    6.47 1.00  1.1e-02
## as.factor(EDUC_CAT)Colleg -0.319397 0.088353 0.088311   13.07 1.00  3.0e-04
## as.factor(MARRY)3          0.093424 0.062865 0.062848    2.21 1.00  1.4e-01
## as.factor(MARRY)4          0.161688 0.101983 0.101975    2.51 1.00  1.1e-01
## as.factor(MARRY)5          0.286372 0.145131 0.145113    3.89 1.00  4.8e-02
## as.factor(MARRY)6          0.209858 0.096878 0.096874    4.69 1.00  3.0e-02
## as.factor(MARRY)8          0.251851 0.336471 0.336462    0.56 1.00  4.5e-01
## BMI                       -0.009028 0.004790 0.004790    3.55 1.00  5.9e-02
## AVGSMK                     0.021489 0.001522 0.001522  199.26 1.00  3.0e-45
## as.factor(SIZE_CAT)Small   0.046129 0.069457 0.069446    0.44 1.00  5.1e-01
## as.factor(SIZE_CAT)Medium  0.028528 0.072274 0.072246    0.16 1.00  6.9e-01
## as.factor(SIZE_CAT)Large  -0.007528 0.053610 0.053523    0.02 1.00  8.9e-01
## 
##                           exp(coef) exp(-coef) lower .95 upper .95
## ps(BOOZE)3                   0.6588     1.5179   0.33992    1.2769
## ps(BOOZE)4                   0.5764     1.7349   0.31524    1.0539
## ps(BOOZE)5                   0.6978     1.4331   0.38447    1.2665
## ps(BOOZE)6                   0.7489     1.3352   0.39017    1.4376
## ps(BOOZE)7                   0.9338     1.0709   0.45167    1.9307
## ps(BOOZE)8                   1.1765     0.8500   0.52201    2.6514
## ps(BOOZE)9                   1.3839     0.7226   0.56737    3.3755
## ps(BOOZE)10                  1.6840     0.5938   0.59440    4.7707
## ps(BOOZE)11                  2.0786     0.4811   0.51955    8.3159
## ps(BOOZE)12                  2.4189     0.4134   0.34474   16.9723
## ps(BOOZE)13                  2.6628     0.3755   0.17083   41.5058
## ps(BOOZE)14                  2.9040     0.3443   0.06255  134.8187
## SEX                          0.5396     1.8532   0.48956    0.5948
## AGEYRS                       1.0997     0.9093   1.09376    1.1057
## as.factor(RACE)2             0.9615     1.0400   0.82960    1.1144
## as.factor(RACE)3             0.7234     1.3824   0.48962    1.0687
## as.factor(EDUC_CAT)Some H    0.9965     1.0036   0.88204    1.1257
## as.factor(EDUC_CAT)HS Gra    0.9335     1.0712   0.83391    1.0451
## as.factor(EDUC_CAT)Some C    0.8104     1.2340   0.68915    0.9529
## as.factor(EDUC_CAT)Colleg    0.7266     1.3763   0.61106    0.8640
## as.factor(MARRY)3            1.0979     0.9108   0.97065    1.2419
## as.factor(MARRY)4            1.1755     0.8507   0.96252    1.4356
## as.factor(MARRY)5            1.3316     0.7510   1.00192    1.7697
## as.factor(MARRY)6            1.2335     0.8107   1.02018    1.4914
## as.factor(MARRY)8            1.2864     0.7774   0.66523    2.4876
## BMI                          0.9910     1.0091   0.98175    1.0004
## AVGSMK                       1.0217     0.9787   1.01868    1.0248
## as.factor(SIZE_CAT)Small     1.0472     0.9549   0.91393    1.1999
## as.factor(SIZE_CAT)Medium    1.0289     0.9719   0.89304    1.1855
## as.factor(SIZE_CAT)Large     0.9925     1.0076   0.89351    1.1025
## 
## Iterations: 5 outer, 13 Newton-Raphson
##      Theta= 0.8419894 
## Degrees of freedom for terms= 4 1 1 2 4 5 1 1 3 
## Concordance= 0.78  (se = 0.005 )
## Likelihood ratio test= 2230  on 22.04 df,   p=<2e-16
termplot(cox_nl1, term = 2, se = TRUE,
         xlab = "BOOZE (drinks/week)",
         ylab = "Partial log hazard",
         main = "Nonlinearity Check: BOOZE")

##Higher Order
d <- d %>%
  mutate(booze_2 = BOOZE^2,
         booze_3 = BOOZE^3)

cox_lin <- coxph(Surv(FU, DEATH) ~ BOOZE + SEX + AGEYRS +
               as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
               AVGSMK + as.factor(SIZE_CAT), data = d, ties = 'efron')
cox.zph(cox_lin)
##                      chisq df      p
## BOOZE                6.662  1 0.0098
## SEX                  5.272  1 0.0217
## AGEYRS               2.190  1 0.1389
## as.factor(RACE)      2.306  2 0.3156
## as.factor(EDUC_CAT) 10.650  4 0.0308
## as.factor(MARRY)     2.794  5 0.7317
## BMI                  0.875  1 0.3496
## AVGSMK               1.045  1 0.3067
## as.factor(SIZE_CAT)  4.626  3 0.2014
## GLOBAL              32.417 19 0.0280
plot(cox.zph(cox_lin))

### Model with BOOZE squared
model_quad <- coxph(Surv(FU, DEATH) ~ BOOZE + booze_2 + SEX + AGEYRS +
               as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
               AVGSMK + as.factor(SIZE_CAT), data = d, ties = 'efron')
summary(model_quad)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ BOOZE + booze_2 + SEX + AGEYRS + 
##     as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                       coef  exp(coef)   se(coef)       z
## BOOZE                           -0.0113101  0.9887536  0.0075300  -1.502
## booze_2                          0.0005518  1.0005520  0.0001923   2.869
## SEX                             -0.6104948  0.5430821  0.0495032 -12.332
## AGEYRS                           0.0954759  1.1001824  0.0027669  34.507
## as.factor(RACE)2                -0.0350201  0.9655860  0.0752562  -0.465
## as.factor(RACE)3                -0.3200731  0.7260959  0.1990934  -1.608
## as.factor(EDUC_CAT)Some HS      -0.0028686  0.9971355  0.0622085  -0.046
## as.factor(EDUC_CAT)HS Grad      -0.0741294  0.9285515  0.0575052  -1.289
## as.factor(EDUC_CAT)Some College -0.2184510  0.8037629  0.0825254  -2.647
## as.factor(EDUC_CAT)College+     -0.3288082  0.7197811  0.0881777  -3.729
## as.factor(MARRY)3                0.0946112  1.0992314  0.0628430   1.506
## as.factor(MARRY)4                0.1643223  1.1785941  0.1019554   1.612
## as.factor(MARRY)5                0.2860587  1.3311706  0.1451446   1.971
## as.factor(MARRY)6                0.2118413  1.2359517  0.0968661   2.187
## as.factor(MARRY)8                0.2599211  1.2968278  0.3364359   0.773
## BMI                             -0.0088376  0.9912013  0.0047916  -1.844
## AVGSMK                           0.0214141  1.0216450  0.0015238  14.053
## as.factor(SIZE_CAT)Small town    0.0465273  1.0476267  0.0694580   0.670
## as.factor(SIZE_CAT)Medium city   0.0342347  1.0348274  0.0721842   0.474
## as.factor(SIZE_CAT)Large city    0.0017790  1.0017806  0.0533245   0.033
##                                 Pr(>|z|)    
## BOOZE                           0.133093    
## booze_2                         0.004118 ** 
## SEX                              < 2e-16 ***
## AGEYRS                           < 2e-16 ***
## as.factor(RACE)2                0.641684    
## as.factor(RACE)3                0.107911    
## as.factor(EDUC_CAT)Some HS      0.963220    
## as.factor(EDUC_CAT)HS Grad      0.197367    
## as.factor(EDUC_CAT)Some College 0.008119 ** 
## as.factor(EDUC_CAT)College+     0.000192 ***
## as.factor(MARRY)3               0.132191    
## as.factor(MARRY)4               0.107025    
## as.factor(MARRY)5               0.048741 *  
## as.factor(MARRY)6               0.028746 *  
## as.factor(MARRY)8               0.439775    
## BMI                             0.065127 .  
## AVGSMK                           < 2e-16 ***
## as.factor(SIZE_CAT)Small town   0.502945    
## as.factor(SIZE_CAT)Medium city  0.635309    
## as.factor(SIZE_CAT)Large city   0.973387    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## BOOZE                              0.9888     1.0114    0.9743    1.0035
## booze_2                            1.0006     0.9994    1.0002    1.0009
## SEX                                0.5431     1.8413    0.4929    0.5984
## AGEYRS                             1.1002     0.9089    1.0942    1.1062
## as.factor(RACE)2                   0.9656     1.0356    0.8332    1.1190
## as.factor(RACE)3                   0.7261     1.3772    0.4915    1.0727
## as.factor(EDUC_CAT)Some HS         0.9971     1.0029    0.8827    1.1264
## as.factor(EDUC_CAT)HS Grad         0.9286     1.0769    0.8296    1.0393
## as.factor(EDUC_CAT)Some College    0.8038     1.2441    0.6837    0.9449
## as.factor(EDUC_CAT)College+        0.7198     1.3893    0.6055    0.8556
## as.factor(MARRY)3                  1.0992     0.9097    0.9718    1.2433
## as.factor(MARRY)4                  1.1786     0.8485    0.9651    1.4393
## as.factor(MARRY)5                  1.3312     0.7512    1.0016    1.7692
## as.factor(MARRY)6                  1.2360     0.8091    1.0222    1.4944
## as.factor(MARRY)8                  1.2968     0.7711    0.6707    2.5076
## BMI                                0.9912     1.0089    0.9819    1.0006
## AVGSMK                             1.0216     0.9788    1.0186    1.0247
## as.factor(SIZE_CAT)Small town      1.0476     0.9545    0.9143    1.2004
## as.factor(SIZE_CAT)Medium city     1.0348     0.9663    0.8983    1.1921
## as.factor(SIZE_CAT)Large city      1.0018     0.9982    0.9024    1.1121
## 
## Concordance= 0.78  (se = 0.005 )
## Likelihood ratio test= 2226  on 20 df,   p=<2e-16
## Wald test            = 1609  on 20 df,   p=<2e-16
## Score (logrank) test = 1881  on 20 df,   p=<2e-16
### Compare linear vs quadratic
anova(cox_lin, model_quad)
## Analysis of Deviance Table
##  Cox model: response is  Surv(FU, DEATH)
##  Model 1: ~ BOOZE + SEX + AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT)
##  Model 2: ~ BOOZE + booze_2 + SEX + AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT)
##   loglik  Chisq Df Pr(>|Chi|)  
## 1 -18038                       
## 2 -18035 6.4288  1    0.01123 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
### Model with BOOZE cubed
model_cubic <- coxph(Surv(FU, DEATH) ~ BOOZE + booze_2 + booze_3 + SEX + AGEYRS +
               as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
               AVGSMK + as.factor(SIZE_CAT), data = d, ties = 'efron')
summary(model_cubic)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ BOOZE + booze_2 + booze_3 + 
##     SEX + AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                       coef  exp(coef)   se(coef)       z
## BOOZE                           -2.898e-02  9.714e-01  1.331e-02  -2.178
## booze_2                          1.912e-03  1.002e+00  8.903e-04   2.148
## booze_3                         -1.935e-05  1.000e+00  1.327e-05  -1.458
## SEX                             -6.159e-01  5.401e-01  4.961e-02 -12.416
## AGEYRS                           9.512e-02  1.100e+00  2.771e-03  34.321
## as.factor(RACE)2                -3.733e-02  9.634e-01  7.526e-02  -0.496
## as.factor(RACE)3                -3.220e-01  7.247e-01  1.991e-01  -1.617
## as.factor(EDUC_CAT)Some HS      -3.025e-03  9.970e-01  6.223e-02  -0.049
## as.factor(EDUC_CAT)HS Grad      -6.884e-02  9.335e-01  5.758e-02  -1.196
## as.factor(EDUC_CAT)Some College -2.098e-01  8.108e-01  8.269e-02  -2.537
## as.factor(EDUC_CAT)College+     -3.195e-01  7.265e-01  8.834e-02  -3.617
## as.factor(MARRY)3                9.199e-02  1.096e+00  6.283e-02   1.464
## as.factor(MARRY)4                1.605e-01  1.174e+00  1.020e-01   1.574
## as.factor(MARRY)5                2.850e-01  1.330e+00  1.451e-01   1.964
## as.factor(MARRY)6                2.095e-01  1.233e+00  9.688e-02   2.163
## as.factor(MARRY)8                2.534e-01  1.288e+00  3.365e-01   0.753
## BMI                             -9.002e-03  9.910e-01  4.792e-03  -1.879
## AVGSMK                           2.148e-02  1.022e+00  1.522e-03  14.116
## as.factor(SIZE_CAT)Small town    4.760e-02  1.049e+00  6.944e-02   0.686
## as.factor(SIZE_CAT)Medium city   2.953e-02  1.030e+00  7.225e-02   0.409
## as.factor(SIZE_CAT)Large city   -6.133e-03  9.939e-01  5.354e-02  -0.115
##                                 Pr(>|z|)    
## BOOZE                           0.029431 *  
## booze_2                         0.031697 *  
## booze_3                         0.144918    
## SEX                              < 2e-16 ***
## AGEYRS                           < 2e-16 ***
## as.factor(RACE)2                0.619852    
## as.factor(RACE)3                0.105850    
## as.factor(EDUC_CAT)Some HS      0.961230    
## as.factor(EDUC_CAT)HS Grad      0.231875    
## as.factor(EDUC_CAT)Some College 0.011191 *  
## as.factor(EDUC_CAT)College+     0.000298 ***
## as.factor(MARRY)3               0.143176    
## as.factor(MARRY)4               0.115572    
## as.factor(MARRY)5               0.049512 *  
## as.factor(MARRY)6               0.030540 *  
## as.factor(MARRY)8               0.451365    
## BMI                             0.060287 .  
## AVGSMK                           < 2e-16 ***
## as.factor(SIZE_CAT)Small town   0.492980    
## as.factor(SIZE_CAT)Medium city  0.682723    
## as.factor(SIZE_CAT)Large city   0.908811    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## BOOZE                              0.9714     1.0294    0.9464    0.9971
## booze_2                            1.0019     0.9981    1.0002    1.0037
## booze_3                            1.0000     1.0000    1.0000    1.0000
## SEX                                0.5401     1.8514    0.4901    0.5953
## AGEYRS                             1.0998     0.9093    1.0938    1.1058
## as.factor(RACE)2                   0.9634     1.0380    0.8312    1.1165
## as.factor(RACE)3                   0.7247     1.3798    0.4906    1.0706
## as.factor(EDUC_CAT)Some HS         0.9970     1.0030    0.8825    1.1263
## as.factor(EDUC_CAT)HS Grad         0.9335     1.0713    0.8339    1.0450
## as.factor(EDUC_CAT)Some College    0.8108     1.2334    0.6895    0.9534
## as.factor(EDUC_CAT)College+        0.7265     1.3765    0.6110    0.8638
## as.factor(MARRY)3                  1.0964     0.9121    0.9693    1.2400
## as.factor(MARRY)4                  1.1741     0.8517    0.9614    1.4338
## as.factor(MARRY)5                  1.3298     0.7520    1.0006    1.7673
## as.factor(MARRY)6                  1.2331     0.8110    1.0199    1.4910
## as.factor(MARRY)8                  1.2884     0.7762    0.6663    2.4914
## BMI                                0.9910     1.0090    0.9818    1.0004
## AVGSMK                             1.0217     0.9787    1.0187    1.0248
## as.factor(SIZE_CAT)Small town      1.0488     0.9535    0.9153    1.2017
## as.factor(SIZE_CAT)Medium city     1.0300     0.9709    0.8940    1.1867
## as.factor(SIZE_CAT)Large city      0.9939     1.0062    0.8949    1.1039
## 
## Concordance= 0.78  (se = 0.005 )
## Likelihood ratio test= 2228  on 21 df,   p=<2e-16
## Wald test            = 1617  on 21 df,   p=<2e-16
## Score (logrank) test = 1891  on 21 df,   p=<2e-16
### Compare linear vs cubic
anova(cox_lin, model_cubic)
## Analysis of Deviance Table
##  Cox model: response is  Surv(FU, DEATH)
##  Model 1: ~ BOOZE + SEX + AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT)
##  Model 2: ~ BOOZE + booze_2 + booze_3 + SEX + AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT)
##   loglik  Chisq Df Pr(>|Chi|)   
## 1 -18038                        
## 2 -18034 9.3269  2   0.009434 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#Adjusted Cox regression with SEX
cox <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q) + SEX + AGEYRS +
               as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
               AVGSMK + as.factor(SIZE_CAT), data = d, ties='efron')
summary(cox)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) + SEX + 
##     AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                       coef  exp(coef)   se(coef)       z
## as.factor(BOOZE_q)0–0.5/week     0.0009412  1.0009416  0.0757507   0.012
## as.factor(BOOZE_q)0.5–2/week    -0.1644537  0.8483570  0.0653782  -2.515
## as.factor(BOOZE_q)>2/week       -0.1056287  0.8997587  0.0582319  -1.814
## SEX                             -0.6351905  0.5298345  0.0497191 -12.776
## AGEYRS                           0.0946933  1.0993217  0.0027755  34.118
## as.factor(RACE)2                -0.0430909  0.9578244  0.0753213  -0.572
## as.factor(RACE)3                -0.3442268  0.7087681  0.1992368  -1.728
## as.factor(EDUC_CAT)Some HS       0.0042420  1.0042510  0.0621828   0.068
## as.factor(EDUC_CAT)HS Grad      -0.0616603  0.9402022  0.0576978  -1.069
## as.factor(EDUC_CAT)Some College -0.2046550  0.8149284  0.0828308  -2.471
## as.factor(EDUC_CAT)College+     -0.3173947  0.7280433  0.0884025  -3.590
## as.factor(MARRY)3                0.0994564  1.1045703  0.0628812   1.582
## as.factor(MARRY)4                0.1603845  1.1739622  0.1020528   1.572
## as.factor(MARRY)5                0.2896492  1.3359587  0.1451368   1.996
## as.factor(MARRY)6                0.2144900  1.2392297  0.0968847   2.214
## as.factor(MARRY)8                0.2506990  1.2849233  0.3364712   0.745
## BMI                             -0.0089585  0.9910815  0.0047857  -1.872
## AVGSMK                           0.0215961  1.0218310  0.0015225  14.185
## as.factor(SIZE_CAT)Small town    0.0420737  1.0429714  0.0694660   0.606
## as.factor(SIZE_CAT)Medium city   0.0185098  1.0186822  0.0724548   0.255
## as.factor(SIZE_CAT)Large city   -0.0204642  0.9797437  0.0540369  -0.379
##                                 Pr(>|z|)    
## as.factor(BOOZE_q)0–0.5/week     0.99009    
## as.factor(BOOZE_q)0.5–2/week     0.01189 *  
## as.factor(BOOZE_q)>2/week        0.06969 .  
## SEX                              < 2e-16 ***
## AGEYRS                           < 2e-16 ***
## as.factor(RACE)2                 0.56726    
## as.factor(RACE)3                 0.08404 .  
## as.factor(EDUC_CAT)Some HS       0.94561    
## as.factor(EDUC_CAT)HS Grad       0.28522    
## as.factor(EDUC_CAT)Some College  0.01348 *  
## as.factor(EDUC_CAT)College+      0.00033 ***
## as.factor(MARRY)3                0.11373    
## as.factor(MARRY)4                0.11605    
## as.factor(MARRY)5                0.04597 *  
## as.factor(MARRY)6                0.02684 *  
## as.factor(MARRY)8                0.45622    
## BMI                              0.06122 .  
## AVGSMK                           < 2e-16 ***
## as.factor(SIZE_CAT)Small town    0.54473    
## as.factor(SIZE_CAT)Medium city   0.79836    
## as.factor(SIZE_CAT)Large city    0.70490    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week       1.0009     0.9991    0.8628    1.1611
## as.factor(BOOZE_q)0.5–2/week       0.8484     1.1787    0.7463    0.9643
## as.factor(BOOZE_q)>2/week          0.8998     1.1114    0.8027    1.0085
## SEX                                0.5298     1.8874    0.4806    0.5841
## AGEYRS                             1.0993     0.9097    1.0934    1.1053
## as.factor(RACE)2                   0.9578     1.0440    0.8264    1.1102
## as.factor(RACE)3                   0.7088     1.4109    0.4796    1.0474
## as.factor(EDUC_CAT)Some HS         1.0043     0.9958    0.8890    1.1344
## as.factor(EDUC_CAT)HS Grad         0.9402     1.0636    0.8397    1.0528
## as.factor(EDUC_CAT)Some College    0.8149     1.2271    0.6928    0.9586
## as.factor(EDUC_CAT)College+        0.7280     1.3735    0.6122    0.8658
## as.factor(MARRY)3                  1.1046     0.9053    0.9765    1.2494
## as.factor(MARRY)4                  1.1740     0.8518    0.9611    1.4339
## as.factor(MARRY)5                  1.3360     0.7485    1.0052    1.7756
## as.factor(MARRY)6                  1.2392     0.8070    1.0249    1.4984
## as.factor(MARRY)8                  1.2849     0.7783    0.6645    2.4847
## BMI                                0.9911     1.0090    0.9818    1.0004
## AVGSMK                             1.0218     0.9786    1.0188    1.0249
## as.factor(SIZE_CAT)Small town      1.0430     0.9588    0.9102    1.1951
## as.factor(SIZE_CAT)Medium city     1.0187     0.9817    0.8838    1.1741
## as.factor(SIZE_CAT)Large city      0.9797     1.0207    0.8813    1.0892
## 
## Concordance= 0.78  (se = 0.005 )
## Likelihood ratio test= 2226  on 21 df,   p=<2e-16
## Wald test            = 1614  on 21 df,   p=<2e-16
## Score (logrank) test = 1884  on 21 df,   p=<2e-16
cox.zph(cox)
##                     chisq df      p
## as.factor(BOOZE_q)  12.05  3 0.0072
## SEX                  5.21  1 0.0224
## AGEYRS               2.13  1 0.1440
## as.factor(RACE)      2.34  2 0.3102
## as.factor(EDUC_CAT) 10.75  4 0.0295
## as.factor(MARRY)     2.73  5 0.7424
## BMI                  0.91  1 0.3401
## AVGSMK               1.07  1 0.3019
## as.factor(SIZE_CAT)  4.65  3 0.1990
## GLOBAL              36.60 21 0.0187
plot(cox.zph(cox))

#Product term with SEX Cox regression
##Categorical BOOZE
cox_product <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q)*SEX + AGEYRS +
               as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
               AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
summary(cox_product)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) * SEX + 
##     AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                       coef exp(coef)  se(coef)       z Pr(>|z|)
## as.factor(BOOZE_q)0–0.5/week      0.078561  1.081729  0.236440   0.332  0.73969
## as.factor(BOOZE_q)0.5–2/week     -0.181241  0.834234  0.194007  -0.934  0.35020
## as.factor(BOOZE_q)>2/week        -0.236482  0.789400  0.166699  -1.419  0.15601
## SEX                              -0.651654  0.521183  0.064827 -10.052  < 2e-16
## AGEYRS                            0.094710  1.099340  0.002777  34.106  < 2e-16
## as.factor(RACE)2                 -0.043171  0.957748  0.075375  -0.573  0.56682
## as.factor(RACE)3                 -0.344107  0.708853  0.199241  -1.727  0.08415
## as.factor(EDUC_CAT)Some HS        0.004468  1.004478  0.062187   0.072  0.94273
## as.factor(EDUC_CAT)HS Grad       -0.061866  0.940009  0.057731  -1.072  0.28389
## as.factor(EDUC_CAT)Some College  -0.205913  0.813904  0.082887  -2.484  0.01298
## as.factor(EDUC_CAT)College+      -0.319003  0.726873  0.088438  -3.607  0.00031
## as.factor(MARRY)3                 0.101557  1.106893  0.062921   1.614  0.10652
## as.factor(MARRY)4                 0.158329  1.171552  0.102083   1.551  0.12090
## as.factor(MARRY)5                 0.293233  1.340755  0.145186   2.020  0.04341
## as.factor(MARRY)6                 0.215696  1.240726  0.096902   2.226  0.02602
## as.factor(MARRY)8                 0.251173  1.285533  0.336770   0.746  0.45577
## BMI                              -0.008623  0.991414  0.004812  -1.792  0.07317
## AVGSMK                            0.021598  1.021833  0.001523  14.184  < 2e-16
## as.factor(SIZE_CAT)Small town     0.043400  1.044355  0.069478   0.625  0.53220
## as.factor(SIZE_CAT)Medium city    0.019116  1.019300  0.072460   0.264  0.79192
## as.factor(SIZE_CAT)Large city    -0.020824  0.979391  0.054054  -0.385  0.70005
## as.factor(BOOZE_q)0–0.5/week:SEX -0.052104  0.949230  0.150466  -0.346  0.72913
## as.factor(BOOZE_q)0.5–2/week:SEX  0.010711  1.010768  0.131179   0.082  0.93493
## as.factor(BOOZE_q)>2/week:SEX     0.103829  1.109411  0.120335   0.863  0.38823
##                                     
## as.factor(BOOZE_q)0–0.5/week        
## as.factor(BOOZE_q)0.5–2/week        
## as.factor(BOOZE_q)>2/week           
## SEX                              ***
## AGEYRS                           ***
## as.factor(RACE)2                    
## as.factor(RACE)3                 .  
## as.factor(EDUC_CAT)Some HS          
## as.factor(EDUC_CAT)HS Grad          
## as.factor(EDUC_CAT)Some College  *  
## as.factor(EDUC_CAT)College+      ***
## as.factor(MARRY)3                   
## as.factor(MARRY)4                   
## as.factor(MARRY)5                *  
## as.factor(MARRY)6                *  
## as.factor(MARRY)8                   
## BMI                              .  
## AVGSMK                           ***
## as.factor(SIZE_CAT)Small town       
## as.factor(SIZE_CAT)Medium city      
## as.factor(SIZE_CAT)Large city       
## as.factor(BOOZE_q)0–0.5/week:SEX    
## as.factor(BOOZE_q)0.5–2/week:SEX    
## as.factor(BOOZE_q)>2/week:SEX       
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                  exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week        1.0817     0.9244    0.6806    1.7194
## as.factor(BOOZE_q)0.5–2/week        0.8342     1.1987    0.5704    1.2202
## as.factor(BOOZE_q)>2/week           0.7894     1.2668    0.5694    1.0944
## SEX                                 0.5212     1.9187    0.4590    0.5918
## AGEYRS                              1.0993     0.9096    1.0934    1.1053
## as.factor(RACE)2                    0.9577     1.0441    0.8262    1.1102
## as.factor(RACE)3                    0.7089     1.4107    0.4797    1.0475
## as.factor(EDUC_CAT)Some HS          1.0045     0.9955    0.8892    1.1347
## as.factor(EDUC_CAT)HS Grad          0.9400     1.0638    0.8394    1.0526
## as.factor(EDUC_CAT)Some College     0.8139     1.2286    0.6919    0.9575
## as.factor(EDUC_CAT)College+         0.7269     1.3758    0.6112    0.8644
## as.factor(MARRY)3                   1.1069     0.9034    0.9785    1.2522
## as.factor(MARRY)4                   1.1716     0.8536    0.9591    1.4310
## as.factor(MARRY)5                   1.3408     0.7458    1.0087    1.7821
## as.factor(MARRY)6                   1.2407     0.8060    1.0261    1.5002
## as.factor(MARRY)8                   1.2855     0.7779    0.6644    2.4874
## BMI                                 0.9914     1.0087    0.9821    1.0008
## AVGSMK                              1.0218     0.9786    1.0188    1.0249
## as.factor(SIZE_CAT)Small town       1.0444     0.9575    0.9114    1.1967
## as.factor(SIZE_CAT)Medium city      1.0193     0.9811    0.8843    1.1748
## as.factor(SIZE_CAT)Large city       0.9794     1.0210    0.8809    1.0888
## as.factor(BOOZE_q)0–0.5/week:SEX    0.9492     1.0535    0.7068    1.2748
## as.factor(BOOZE_q)0.5–2/week:SEX    1.0108     0.9893    0.7816    1.3071
## as.factor(BOOZE_q)>2/week:SEX       1.1094     0.9014    0.8763    1.4045
## 
## Concordance= 0.78  (se = 0.005 )
## Likelihood ratio test= 2227  on 24 df,   p=<2e-16
## Wald test            = 1617  on 24 df,   p=<2e-16
## Score (logrank) test = 1897  on 24 df,   p=<2e-16
cox.zph(cox_product)
##                         chisq df      p
## as.factor(BOOZE_q)     11.911  3 0.0077
## SEX                     5.192  1 0.0227
## AGEYRS                  2.122  1 0.1452
## as.factor(RACE)         2.359  2 0.3075
## as.factor(EDUC_CAT)    10.722  4 0.0299
## as.factor(MARRY)        2.727  5 0.7420
## BMI                     0.898  1 0.3434
## AVGSMK                  1.051  1 0.3054
## as.factor(SIZE_CAT)     4.647  3 0.1996
## as.factor(BOOZE_q):SEX 15.535  3 0.0014
## GLOBAL                 36.895 24 0.0448
plot(cox.zph(cox_product))

##Continuous BOOZE
cox_product1 <- coxph(Surv(FU, DEATH) ~ BOOZE*SEX + AGEYRS +
               as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
               AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
summary(cox_product)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) * SEX + 
##     AGEYRS + as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                       coef exp(coef)  se(coef)       z Pr(>|z|)
## as.factor(BOOZE_q)0–0.5/week      0.078561  1.081729  0.236440   0.332  0.73969
## as.factor(BOOZE_q)0.5–2/week     -0.181241  0.834234  0.194007  -0.934  0.35020
## as.factor(BOOZE_q)>2/week        -0.236482  0.789400  0.166699  -1.419  0.15601
## SEX                              -0.651654  0.521183  0.064827 -10.052  < 2e-16
## AGEYRS                            0.094710  1.099340  0.002777  34.106  < 2e-16
## as.factor(RACE)2                 -0.043171  0.957748  0.075375  -0.573  0.56682
## as.factor(RACE)3                 -0.344107  0.708853  0.199241  -1.727  0.08415
## as.factor(EDUC_CAT)Some HS        0.004468  1.004478  0.062187   0.072  0.94273
## as.factor(EDUC_CAT)HS Grad       -0.061866  0.940009  0.057731  -1.072  0.28389
## as.factor(EDUC_CAT)Some College  -0.205913  0.813904  0.082887  -2.484  0.01298
## as.factor(EDUC_CAT)College+      -0.319003  0.726873  0.088438  -3.607  0.00031
## as.factor(MARRY)3                 0.101557  1.106893  0.062921   1.614  0.10652
## as.factor(MARRY)4                 0.158329  1.171552  0.102083   1.551  0.12090
## as.factor(MARRY)5                 0.293233  1.340755  0.145186   2.020  0.04341
## as.factor(MARRY)6                 0.215696  1.240726  0.096902   2.226  0.02602
## as.factor(MARRY)8                 0.251173  1.285533  0.336770   0.746  0.45577
## BMI                              -0.008623  0.991414  0.004812  -1.792  0.07317
## AVGSMK                            0.021598  1.021833  0.001523  14.184  < 2e-16
## as.factor(SIZE_CAT)Small town     0.043400  1.044355  0.069478   0.625  0.53220
## as.factor(SIZE_CAT)Medium city    0.019116  1.019300  0.072460   0.264  0.79192
## as.factor(SIZE_CAT)Large city    -0.020824  0.979391  0.054054  -0.385  0.70005
## as.factor(BOOZE_q)0–0.5/week:SEX -0.052104  0.949230  0.150466  -0.346  0.72913
## as.factor(BOOZE_q)0.5–2/week:SEX  0.010711  1.010768  0.131179   0.082  0.93493
## as.factor(BOOZE_q)>2/week:SEX     0.103829  1.109411  0.120335   0.863  0.38823
##                                     
## as.factor(BOOZE_q)0–0.5/week        
## as.factor(BOOZE_q)0.5–2/week        
## as.factor(BOOZE_q)>2/week           
## SEX                              ***
## AGEYRS                           ***
## as.factor(RACE)2                    
## as.factor(RACE)3                 .  
## as.factor(EDUC_CAT)Some HS          
## as.factor(EDUC_CAT)HS Grad          
## as.factor(EDUC_CAT)Some College  *  
## as.factor(EDUC_CAT)College+      ***
## as.factor(MARRY)3                   
## as.factor(MARRY)4                   
## as.factor(MARRY)5                *  
## as.factor(MARRY)6                *  
## as.factor(MARRY)8                   
## BMI                              .  
## AVGSMK                           ***
## as.factor(SIZE_CAT)Small town       
## as.factor(SIZE_CAT)Medium city      
## as.factor(SIZE_CAT)Large city       
## as.factor(BOOZE_q)0–0.5/week:SEX    
## as.factor(BOOZE_q)0.5–2/week:SEX    
## as.factor(BOOZE_q)>2/week:SEX       
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                  exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week        1.0817     0.9244    0.6806    1.7194
## as.factor(BOOZE_q)0.5–2/week        0.8342     1.1987    0.5704    1.2202
## as.factor(BOOZE_q)>2/week           0.7894     1.2668    0.5694    1.0944
## SEX                                 0.5212     1.9187    0.4590    0.5918
## AGEYRS                              1.0993     0.9096    1.0934    1.1053
## as.factor(RACE)2                    0.9577     1.0441    0.8262    1.1102
## as.factor(RACE)3                    0.7089     1.4107    0.4797    1.0475
## as.factor(EDUC_CAT)Some HS          1.0045     0.9955    0.8892    1.1347
## as.factor(EDUC_CAT)HS Grad          0.9400     1.0638    0.8394    1.0526
## as.factor(EDUC_CAT)Some College     0.8139     1.2286    0.6919    0.9575
## as.factor(EDUC_CAT)College+         0.7269     1.3758    0.6112    0.8644
## as.factor(MARRY)3                   1.1069     0.9034    0.9785    1.2522
## as.factor(MARRY)4                   1.1716     0.8536    0.9591    1.4310
## as.factor(MARRY)5                   1.3408     0.7458    1.0087    1.7821
## as.factor(MARRY)6                   1.2407     0.8060    1.0261    1.5002
## as.factor(MARRY)8                   1.2855     0.7779    0.6644    2.4874
## BMI                                 0.9914     1.0087    0.9821    1.0008
## AVGSMK                              1.0218     0.9786    1.0188    1.0249
## as.factor(SIZE_CAT)Small town       1.0444     0.9575    0.9114    1.1967
## as.factor(SIZE_CAT)Medium city      1.0193     0.9811    0.8843    1.1748
## as.factor(SIZE_CAT)Large city       0.9794     1.0210    0.8809    1.0888
## as.factor(BOOZE_q)0–0.5/week:SEX    0.9492     1.0535    0.7068    1.2748
## as.factor(BOOZE_q)0.5–2/week:SEX    1.0108     0.9893    0.7816    1.3071
## as.factor(BOOZE_q)>2/week:SEX       1.1094     0.9014    0.8763    1.4045
## 
## Concordance= 0.78  (se = 0.005 )
## Likelihood ratio test= 2227  on 24 df,   p=<2e-16
## Wald test            = 1617  on 24 df,   p=<2e-16
## Score (logrank) test = 1897  on 24 df,   p=<2e-16
cox.zph(cox_product1)
##                      chisq df      p
## BOOZE                6.705  1 0.0096
## SEX                  5.273  1 0.0217
## AGEYRS               2.191  1 0.1389
## as.factor(RACE)      2.304  2 0.3161
## as.factor(EDUC_CAT) 10.653  4 0.0307
## as.factor(MARRY)     2.792  5 0.7320
## BMI                  0.876  1 0.3493
## AVGSMK               1.047  1 0.3061
## as.factor(SIZE_CAT)  4.627  3 0.2012
## BOOZE:SEX            8.921  1 0.0028
## GLOBAL              32.597 20 0.0373
plot(cox.zph(cox_product))

#Stratified model by SEX
##Categorical BOOZE
cox_strata_cat <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q) + AGEYRS + as.factor(RACE) + 
                   as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
                   AVGSMK + as.factor(SIZE_CAT) + strata(SEX), data = d, ties = 'efron')
summary(cox_strata_cat)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) + AGEYRS + 
##     as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT) + strata(SEX), data = d, 
##     ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                       coef  exp(coef)   se(coef)      z
## as.factor(BOOZE_q)0–0.5/week     0.0005982  1.0005984  0.0757495  0.008
## as.factor(BOOZE_q)0.5–2/week    -0.1645524  0.8482733  0.0653731 -2.517
## as.factor(BOOZE_q)>2/week       -0.1041216  0.9011157  0.0582166 -1.789
## AGEYRS                           0.0944693  1.0990755  0.0027744 34.050
## as.factor(RACE)2                -0.0427210  0.9581787  0.0753318 -0.567
## as.factor(RACE)3                -0.3424003  0.7100639  0.1992445 -1.718
## as.factor(EDUC_CAT)Some HS       0.0054167  1.0054314  0.0621896  0.087
## as.factor(EDUC_CAT)HS Grad      -0.0613644  0.9404804  0.0576961 -1.064
## as.factor(EDUC_CAT)Some College -0.2042635  0.8152475  0.0828347 -2.466
## as.factor(EDUC_CAT)College+     -0.3152965  0.7295726  0.0884112 -3.566
## as.factor(MARRY)3                0.1004634  1.1056832  0.0628689  1.598
## as.factor(MARRY)4                0.1585617  1.1718242  0.1020662  1.554
## as.factor(MARRY)5                0.2896007  1.3358940  0.1451502  1.995
## as.factor(MARRY)6                0.2132433  1.2376857  0.0968963  2.201
## as.factor(MARRY)8                0.2564887  1.2923842  0.3364842  0.762
## BMI                             -0.0089119  0.9911277  0.0047851 -1.862
## AVGSMK                           0.0215104  1.0217434  0.0015226 14.127
## as.factor(SIZE_CAT)Small town    0.0415937  1.0424708  0.0694716  0.599
## as.factor(SIZE_CAT)Medium city   0.0170622  1.0172086  0.0724611  0.235
## as.factor(SIZE_CAT)Large city   -0.0206079  0.9796030  0.0540481 -0.381
##                                 Pr(>|z|)    
## as.factor(BOOZE_q)0–0.5/week    0.993699    
## as.factor(BOOZE_q)0.5–2/week    0.011832 *  
## as.factor(BOOZE_q)>2/week       0.073692 .  
## AGEYRS                           < 2e-16 ***
## as.factor(RACE)2                0.570643    
## as.factor(RACE)3                0.085707 .  
## as.factor(EDUC_CAT)Some HS      0.930592    
## as.factor(EDUC_CAT)HS Grad      0.287519    
## as.factor(EDUC_CAT)Some College 0.013666 *  
## as.factor(EDUC_CAT)College+     0.000362 ***
## as.factor(MARRY)3               0.110047    
## as.factor(MARRY)4               0.120300    
## as.factor(MARRY)5               0.046023 *  
## as.factor(MARRY)6               0.027755 *  
## as.factor(MARRY)8               0.445904    
## BMI                             0.062543 .  
## AVGSMK                           < 2e-16 ***
## as.factor(SIZE_CAT)Small town   0.549363    
## as.factor(SIZE_CAT)Medium city  0.813846    
## as.factor(SIZE_CAT)Large city   0.702990    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week       1.0006     0.9994    0.8625    1.1607
## as.factor(BOOZE_q)0.5–2/week       0.8483     1.1789    0.7463    0.9642
## as.factor(BOOZE_q)>2/week          0.9011     1.1097    0.8039    1.0100
## AGEYRS                             1.0991     0.9099    1.0931    1.1051
## as.factor(RACE)2                   0.9582     1.0436    0.8267    1.1106
## as.factor(RACE)3                   0.7101     1.4083    0.4805    1.0493
## as.factor(EDUC_CAT)Some HS         1.0054     0.9946    0.8901    1.1358
## as.factor(EDUC_CAT)HS Grad         0.9405     1.0633    0.8399    1.0531
## as.factor(EDUC_CAT)Some College    0.8152     1.2266    0.6931    0.9590
## as.factor(EDUC_CAT)College+        0.7296     1.3707    0.6135    0.8676
## as.factor(MARRY)3                  1.1057     0.9044    0.9775    1.2507
## as.factor(MARRY)4                  1.1718     0.8534    0.9594    1.4313
## as.factor(MARRY)5                  1.3359     0.7486    1.0051    1.7755
## as.factor(MARRY)6                  1.2377     0.8080    1.0236    1.4965
## as.factor(MARRY)8                  1.2924     0.7738    0.6683    2.4992
## BMI                                0.9911     1.0090    0.9819    1.0005
## AVGSMK                             1.0217     0.9787    1.0187    1.0248
## as.factor(SIZE_CAT)Small town      1.0425     0.9593    0.9098    1.1945
## as.factor(SIZE_CAT)Medium city     1.0172     0.9831    0.8825    1.1724
## as.factor(SIZE_CAT)Large city      0.9796     1.0208    0.8811    1.0891
## 
## Concordance= 0.769  (se = 0.005 )
## Likelihood ratio test= 2057  on 20 df,   p=<2e-16
## Wald test            = 1440  on 20 df,   p=<2e-16
## Score (logrank) test = 1722  on 20 df,   p=<2e-16
cox.zph(cox_strata_cat)
##                     chisq df       p
## as.factor(BOOZE_q)  17.11  3 0.00067
## AGEYRS               2.66  1 0.10275
## as.factor(RACE)      2.20  2 0.33283
## as.factor(EDUC_CAT) 10.19  4 0.03733
## as.factor(MARRY)     2.58  5 0.76512
## BMI                  1.35  1 0.24580
## AVGSMK               1.85  1 0.17337
## as.factor(SIZE_CAT)  4.78  3 0.18882
## GLOBAL              31.60 20 0.04780
plot(cox.zph(cox_strata_cat))

cox_strata_cat1 <- coxph(Surv(FU, DEATH) ~ strata(BOOZE_q, SEX) + AGEYRS + as.factor(RACE) + 
                   as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
                   AVGSMK + as.factor(SIZE_CAT), data = d, ties = 'efron')
summary(cox_strata_cat1)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ strata(BOOZE_q, SEX) + AGEYRS + 
##     as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                      coef exp(coef)  se(coef)      z Pr(>|z|)
## AGEYRS                           0.094721  1.099352  0.002780 34.077  < 2e-16
## as.factor(RACE)2                -0.035983  0.964656  0.075454 -0.477 0.633439
## as.factor(RACE)3                -0.334183  0.715923  0.199265 -1.677 0.093527
## as.factor(EDUC_CAT)Some HS       0.008328  1.008363  0.062215  0.134 0.893516
## as.factor(EDUC_CAT)HS Grad      -0.061364  0.940481  0.057737 -1.063 0.287868
## as.factor(EDUC_CAT)Some College -0.204930  0.814704  0.082938 -2.471 0.013478
## as.factor(EDUC_CAT)College+     -0.317439  0.728011  0.088442 -3.589 0.000332
## as.factor(MARRY)3                0.101433  1.106756  0.062945  1.611 0.107077
## as.factor(MARRY)4                0.157662  1.170771  0.102154  1.543 0.122740
## as.factor(MARRY)5                0.294478  1.342425  0.145248  2.027 0.042621
## as.factor(MARRY)6                0.214020  1.238647  0.096941  2.208 0.027263
## as.factor(MARRY)8                0.266243  1.305052  0.336924  0.790 0.429401
## BMI                             -0.008439  0.991596  0.004805 -1.756 0.079031
## AVGSMK                           0.021585  1.021820  0.001524 14.163  < 2e-16
## as.factor(SIZE_CAT)Small town    0.044737  1.045753  0.069528  0.643 0.519937
## as.factor(SIZE_CAT)Medium city   0.018464  1.018636  0.072537  0.255 0.799071
## as.factor(SIZE_CAT)Large city   -0.017115  0.983030  0.054166 -0.316 0.752017
##                                    
## AGEYRS                          ***
## as.factor(RACE)2                   
## as.factor(RACE)3                .  
## as.factor(EDUC_CAT)Some HS         
## as.factor(EDUC_CAT)HS Grad         
## as.factor(EDUC_CAT)Some College *  
## as.factor(EDUC_CAT)College+     ***
## as.factor(MARRY)3                  
## as.factor(MARRY)4                  
## as.factor(MARRY)5               *  
## as.factor(MARRY)6               *  
## as.factor(MARRY)8                  
## BMI                             .  
## AVGSMK                          ***
## as.factor(SIZE_CAT)Small town      
## as.factor(SIZE_CAT)Medium city     
## as.factor(SIZE_CAT)Large city      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## AGEYRS                             1.0994     0.9096    1.0934    1.1054
## as.factor(RACE)2                   0.9647     1.0366    0.8320    1.1184
## as.factor(RACE)3                   0.7159     1.3968    0.4845    1.0580
## as.factor(EDUC_CAT)Some HS         1.0084     0.9917    0.8926    1.1391
## as.factor(EDUC_CAT)HS Grad         0.9405     1.0633    0.8399    1.0532
## as.factor(EDUC_CAT)Some College    0.8147     1.2274    0.6925    0.9585
## as.factor(EDUC_CAT)College+        0.7280     1.3736    0.6121    0.8658
## as.factor(MARRY)3                  1.1068     0.9035    0.9783    1.2521
## as.factor(MARRY)4                  1.1708     0.8541    0.9583    1.4303
## as.factor(MARRY)5                  1.3424     0.7449    1.0098    1.7845
## as.factor(MARRY)6                  1.2386     0.8073    1.0243    1.4978
## as.factor(MARRY)8                  1.3051     0.7663    0.6743    2.5259
## BMI                                0.9916     1.0085    0.9823    1.0010
## AVGSMK                             1.0218     0.9786    1.0188    1.0249
## as.factor(SIZE_CAT)Small town      1.0458     0.9562    0.9125    1.1984
## as.factor(SIZE_CAT)Medium city     1.0186     0.9817    0.8836    1.1743
## as.factor(SIZE_CAT)Large city      0.9830     1.0173    0.8840    1.0931
## 
## Concordance= 0.756  (se = 0.005 )
## Likelihood ratio test= 1957  on 17 df,   p=<2e-16
## Wald test            = 1386  on 17 df,   p=<2e-16
## Score (logrank) test = 1621  on 17 df,   p=<2e-16
cox.zph(cox_strata_cat1)
##                      chisq df    p
## AGEYRS               0.934  1 0.33
## as.factor(RACE)      1.339  2 0.51
## as.factor(EDUC_CAT)  5.184  4 0.27
## as.factor(MARRY)     2.654  5 0.75
## BMI                  0.659  1 0.42
## AVGSMK               1.075  1 0.30
## as.factor(SIZE_CAT)  4.277  3 0.23
## GLOBAL              14.085 17 0.66
plot(cox.zph(cox_strata_cat1))

##Continuous BOOZE
cox_strata_lin <- coxph(Surv(FU, DEATH) ~ BOOZE + strata(SEX) + AGEYRS + as.factor(RACE) + 
                   as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
                   AVGSMK + as.factor(SIZE_CAT), data = d, ties = 'efron')
summary(cox_strata_lin)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ BOOZE + strata(SEX) + AGEYRS + 
##     as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                      coef exp(coef)  se(coef)      z Pr(>|z|)
## BOOZE                            0.004550  1.004560  0.004521  1.006  0.31420
## AGEYRS                           0.095344  1.100037  0.002766 34.471  < 2e-16
## as.factor(RACE)2                -0.030171  0.970279  0.075247 -0.401  0.68845
## as.factor(RACE)3                -0.313876  0.730610  0.199098 -1.576  0.11491
## as.factor(EDUC_CAT)Some HS      -0.008977  0.991063  0.062170 -0.144  0.88519
## as.factor(EDUC_CAT)HS Grad      -0.084093  0.919346  0.057390 -1.465  0.14284
## as.factor(EDUC_CAT)Some College -0.233060  0.792106  0.082366 -2.830  0.00466
## as.factor(EDUC_CAT)College+     -0.344877  0.708308  0.087952 -3.921 8.81e-05
## as.factor(MARRY)3                0.096325  1.101117  0.062847  1.533  0.12535
## as.factor(MARRY)4                0.167296  1.182104  0.101947  1.641  0.10080
## as.factor(MARRY)5                0.281392  1.324973  0.145178  1.938  0.05259
## as.factor(MARRY)6                0.214993  1.239853  0.096863  2.220  0.02645
## as.factor(MARRY)8                0.276459  1.318452  0.336402  0.822  0.41119
## BMI                             -0.008214  0.991820  0.004784 -1.717  0.08597
## AVGSMK                           0.021192  1.021418  0.001528 13.869  < 2e-16
## as.factor(SIZE_CAT)Small town    0.050405  1.051697  0.069423  0.726  0.46780
## as.factor(SIZE_CAT)Medium city   0.040288  1.041111  0.072116  0.559  0.57639
## as.factor(SIZE_CAT)Large city    0.014944  1.015056  0.053087  0.282  0.77832
##                                    
## BOOZE                              
## AGEYRS                          ***
## as.factor(RACE)2                   
## as.factor(RACE)3                   
## as.factor(EDUC_CAT)Some HS         
## as.factor(EDUC_CAT)HS Grad         
## as.factor(EDUC_CAT)Some College ** 
## as.factor(EDUC_CAT)College+     ***
## as.factor(MARRY)3                  
## as.factor(MARRY)4                  
## as.factor(MARRY)5               .  
## as.factor(MARRY)6               *  
## as.factor(MARRY)8                  
## BMI                             .  
## AVGSMK                          ***
## as.factor(SIZE_CAT)Small town      
## as.factor(SIZE_CAT)Medium city     
## as.factor(SIZE_CAT)Large city      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## BOOZE                              1.0046     0.9955    0.9957    1.0135
## AGEYRS                             1.1000     0.9091    1.0941    1.1060
## as.factor(RACE)2                   0.9703     1.0306    0.8372    1.1245
## as.factor(RACE)3                   0.7306     1.3687    0.4946    1.0793
## as.factor(EDUC_CAT)Some HS         0.9911     1.0090    0.8774    1.1195
## as.factor(EDUC_CAT)HS Grad         0.9193     1.0877    0.8215    1.0288
## as.factor(EDUC_CAT)Some College    0.7921     1.2625    0.6740    0.9309
## as.factor(EDUC_CAT)College+        0.7083     1.4118    0.5962    0.8416
## as.factor(MARRY)3                  1.1011     0.9082    0.9735    1.2455
## as.factor(MARRY)4                  1.1821     0.8459    0.9680    1.4436
## as.factor(MARRY)5                  1.3250     0.7547    0.9969    1.7611
## as.factor(MARRY)6                  1.2399     0.8065    1.0255    1.4991
## as.factor(MARRY)8                  1.3185     0.7585    0.6819    2.5492
## BMI                                0.9918     1.0082    0.9826    1.0012
## AVGSMK                             1.0214     0.9790    1.0184    1.0245
## as.factor(SIZE_CAT)Small town      1.0517     0.9508    0.9179    1.2050
## as.factor(SIZE_CAT)Medium city     1.0411     0.9605    0.9039    1.1992
## as.factor(SIZE_CAT)Large city      1.0151     0.9852    0.9148    1.1264
## 
## Concordance= 0.768  (se = 0.005 )
## Likelihood ratio test= 2050  on 18 df,   p=<2e-16
## Wald test            = 1426  on 18 df,   p=<2e-16
## Score (logrank) test = 1709  on 18 df,   p=<2e-16
cox.zph(cox_strata_lin)
##                     chisq df      p
## BOOZE               10.15  1 0.0014
## AGEYRS               2.72  1 0.0989
## as.factor(RACE)      2.16  2 0.3394
## as.factor(EDUC_CAT) 10.08  4 0.0392
## as.factor(MARRY)     2.62  5 0.7578
## BMI                  1.30  1 0.2546
## AVGSMK               1.84  1 0.1751
## as.factor(SIZE_CAT)  4.77  3 0.1892
## GLOBAL              27.27 18 0.0740
plot(cox.zph(cox_strata_lin))

cox_strata_lin1 <- coxph(Surv(FU, DEATH) ~ strata(BOOZE, SEX) + AGEYRS + as.factor(RACE) + 
                   as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + 
                   AVGSMK + as.factor(SIZE_CAT), data = d, ties = 'efron')
summary(cox_strata_lin1)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ strata(BOOZE, SEX) + AGEYRS + 
##     as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d, ties = "efron")
## 
##   n= 9250, number of events= 2145 
## 
##                                      coef exp(coef)  se(coef)      z Pr(>|z|)
## AGEYRS                           0.094241  1.098824  0.002813 33.507  < 2e-16
## as.factor(RACE)2                -0.055017  0.946469  0.076116 -0.723 0.469794
## as.factor(RACE)3                -0.383644  0.681374  0.200257 -1.916 0.055396
## as.factor(EDUC_CAT)Some HS       0.011292  1.011356  0.062950  0.179 0.857641
## as.factor(EDUC_CAT)HS Grad      -0.057861  0.943781  0.058435 -0.990 0.322085
## as.factor(EDUC_CAT)Some College -0.198715  0.819783  0.083946 -2.367 0.017925
## as.factor(EDUC_CAT)College+     -0.314775  0.729953  0.090355 -3.484 0.000494
## as.factor(MARRY)3                0.102073  1.107464  0.063936  1.596 0.110380
## as.factor(MARRY)4                0.142776  1.153472  0.103765  1.376 0.168835
## as.factor(MARRY)5                0.323350  1.381749  0.146172  2.212 0.026958
## as.factor(MARRY)6                0.218940  1.244757  0.098249  2.228 0.025853
## as.factor(MARRY)8                0.283854  1.328239  0.338939  0.837 0.402323
## BMI                             -0.007542  0.992486  0.004851 -1.555 0.119983
## AVGSMK                           0.021261  1.021489  0.001556 13.665  < 2e-16
## as.factor(SIZE_CAT)Small town    0.034391  1.034989  0.070484  0.488 0.625605
## as.factor(SIZE_CAT)Medium city  -0.002916  0.997088  0.073392 -0.040 0.968307
## as.factor(SIZE_CAT)Large city   -0.039409  0.961358  0.054723 -0.720 0.471432
##                                    
## AGEYRS                          ***
## as.factor(RACE)2                   
## as.factor(RACE)3                .  
## as.factor(EDUC_CAT)Some HS         
## as.factor(EDUC_CAT)HS Grad         
## as.factor(EDUC_CAT)Some College *  
## as.factor(EDUC_CAT)College+     ***
## as.factor(MARRY)3                  
## as.factor(MARRY)4                  
## as.factor(MARRY)5               *  
## as.factor(MARRY)6               *  
## as.factor(MARRY)8                  
## BMI                                
## AVGSMK                          ***
## as.factor(SIZE_CAT)Small town      
## as.factor(SIZE_CAT)Medium city     
## as.factor(SIZE_CAT)Large city      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## AGEYRS                             1.0988     0.9101    1.0928    1.1049
## as.factor(RACE)2                   0.9465     1.0566    0.8153    1.0987
## as.factor(RACE)3                   0.6814     1.4676    0.4602    1.0089
## as.factor(EDUC_CAT)Some HS         1.0114     0.9888    0.8940    1.1442
## as.factor(EDUC_CAT)HS Grad         0.9438     1.0596    0.8416    1.0583
## as.factor(EDUC_CAT)Some College    0.8198     1.2198    0.6954    0.9664
## as.factor(EDUC_CAT)College+        0.7300     1.3700    0.6115    0.8714
## as.factor(MARRY)3                  1.1075     0.9030    0.9770    1.2553
## as.factor(MARRY)4                  1.1535     0.8669    0.9412    1.4136
## as.factor(MARRY)5                  1.3817     0.7237    1.0375    1.8401
## as.factor(MARRY)6                  1.2448     0.8034    1.0267    1.5091
## as.factor(MARRY)8                  1.3282     0.7529    0.6836    2.5810
## BMI                                0.9925     1.0076    0.9831    1.0020
## AVGSMK                             1.0215     0.9790    1.0184    1.0246
## as.factor(SIZE_CAT)Small town      1.0350     0.9662    0.9014    1.1883
## as.factor(SIZE_CAT)Medium city     0.9971     1.0029    0.8635    1.1513
## as.factor(SIZE_CAT)Large city      0.9614     1.0402    0.8636    1.0702
## 
## Concordance= 0.743  (se = 0.007 )
## Likelihood ratio test= 1886  on 17 df,   p=<2e-16
## Wald test            = 1329  on 17 df,   p=<2e-16
## Score (logrank) test = 1555  on 17 df,   p=<2e-16
cox.zph(cox_strata_lin1)
##                      chisq df    p
## AGEYRS               0.690  1 0.41
## as.factor(RACE)      1.622  2 0.44
## as.factor(EDUC_CAT)  6.267  4 0.18
## as.factor(MARRY)     3.156  5 0.68
## BMI                  0.494  1 0.48
## AVGSMK               0.928  1 0.34
## as.factor(SIZE_CAT)  4.369  3 0.22
## GLOBAL              15.499 17 0.56
plot(cox.zph(cox_strata_lin1))

###
cox_men <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q) + 
        AGEYRS + as.factor(RACE) +  as.factor(EDUC_CAT) + 
                    as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT), 
                    data = d[d$SEX == 1, ])
summary(cox_men)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) + AGEYRS + 
##     as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d[d$SEX == 1, 
##     ])
## 
##   n= 4349, number of events= 1258 
## 
##                                      coef exp(coef)  se(coef)      z Pr(>|z|)
## as.factor(BOOZE_q)0–0.5/week     0.030921  1.031404  0.106069  0.292 0.770658
## as.factor(BOOZE_q)0.5–2/week    -0.155038  0.856382  0.084044 -1.845 0.065076
## as.factor(BOOZE_q)>2/week       -0.121964  0.885180  0.070185 -1.738 0.082253
## AGEYRS                           0.094329  1.098921  0.003591 26.269  < 2e-16
## as.factor(RACE)2                -0.124606  0.882844  0.099122 -1.257 0.208717
## as.factor(RACE)3                -0.547403  0.578450  0.262715 -2.084 0.037193
## as.factor(EDUC_CAT)Some HS       0.041982  1.042875  0.080265  0.523 0.600949
## as.factor(EDUC_CAT)HS Grad      -0.066953  0.935239  0.076742 -0.872 0.382965
## as.factor(EDUC_CAT)Some College -0.182969  0.832794  0.107612 -1.700 0.089081
## as.factor(EDUC_CAT)College+     -0.433200  0.648431  0.115983 -3.735 0.000188
## as.factor(MARRY)3                0.129384  1.138127  0.112721  1.148 0.251039
## as.factor(MARRY)4                0.389988  1.476963  0.130698  2.984 0.002846
## as.factor(MARRY)5                0.329985  1.390947  0.184067  1.793 0.073015
## as.factor(MARRY)6                0.341293  1.406765  0.125603  2.717 0.006583
## as.factor(MARRY)8                0.483891  1.622374  0.452610  1.069 0.285019
## BMI                             -0.018552  0.981619  0.007291 -2.545 0.010938
## AVGSMK                           0.019458  1.019648  0.001869 10.412  < 2e-16
## as.factor(SIZE_CAT)Small town    0.049592  1.050843  0.092874  0.534 0.593357
## as.factor(SIZE_CAT)Medium city   0.109276  1.115470  0.096604  1.131 0.257979
## as.factor(SIZE_CAT)Large city   -0.032266  0.968249  0.070377 -0.458 0.646617
##                                    
## as.factor(BOOZE_q)0–0.5/week       
## as.factor(BOOZE_q)0.5–2/week    .  
## as.factor(BOOZE_q)>2/week       .  
## AGEYRS                          ***
## as.factor(RACE)2                   
## as.factor(RACE)3                *  
## as.factor(EDUC_CAT)Some HS         
## as.factor(EDUC_CAT)HS Grad         
## as.factor(EDUC_CAT)Some College .  
## as.factor(EDUC_CAT)College+     ***
## as.factor(MARRY)3                  
## as.factor(MARRY)4               ** 
## as.factor(MARRY)5               .  
## as.factor(MARRY)6               ** 
## as.factor(MARRY)8                  
## BMI                             *  
## AVGSMK                          ***
## as.factor(SIZE_CAT)Small town      
## as.factor(SIZE_CAT)Medium city     
## as.factor(SIZE_CAT)Large city      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week       1.0314     0.9696    0.8378    1.2697
## as.factor(BOOZE_q)0.5–2/week       0.8564     1.1677    0.7263    1.0097
## as.factor(BOOZE_q)>2/week          0.8852     1.1297    0.7714    1.0157
## AGEYRS                             1.0989     0.9100    1.0912    1.1067
## as.factor(RACE)2                   0.8828     1.1327    0.7270    1.0722
## as.factor(RACE)3                   0.5785     1.7288    0.3457    0.9680
## as.factor(EDUC_CAT)Some HS         1.0429     0.9589    0.8911    1.2205
## as.factor(EDUC_CAT)HS Grad         0.9352     1.0692    0.8046    1.0870
## as.factor(EDUC_CAT)Some College    0.8328     1.2008    0.6744    1.0283
## as.factor(EDUC_CAT)College+        0.6484     1.5422    0.5166    0.8139
## as.factor(MARRY)3                  1.1381     0.8786    0.9125    1.4195
## as.factor(MARRY)4                  1.4770     0.6771    1.1432    1.9082
## as.factor(MARRY)5                  1.3909     0.7189    0.9697    1.9952
## as.factor(MARRY)6                  1.4068     0.7109    1.0998    1.7994
## as.factor(MARRY)8                  1.6224     0.6164    0.6682    3.9392
## BMI                                0.9816     1.0187    0.9677    0.9957
## AVGSMK                             1.0196     0.9807    1.0159    1.0234
## as.factor(SIZE_CAT)Small town      1.0508     0.9516    0.8760    1.2606
## as.factor(SIZE_CAT)Medium city     1.1155     0.8965    0.9231    1.3480
## as.factor(SIZE_CAT)Large city      0.9682     1.0328    0.8435    1.1115
## 
## Concordance= 0.776  (se = 0.006 )
## Likelihood ratio test= 1255  on 20 df,   p=<2e-16
## Wald test            = 883  on 20 df,   p=<2e-16
## Score (logrank) test = 1063  on 20 df,   p=<2e-16
cox.zph(cox_men)
##                        chisq df      p
## as.factor(BOOZE_q)  1.14e+01  3 0.0098
## AGEYRS              5.50e+00  1 0.0190
## as.factor(RACE)     5.63e-01  2 0.7548
## as.factor(EDUC_CAT) 5.16e+00  4 0.2715
## as.factor(MARRY)    1.65e+00  5 0.8952
## BMI                 6.99e-04  1 0.9789
## AVGSMK              5.39e-02  1 0.8164
## as.factor(SIZE_CAT) 3.73e+00  3 0.2925
## GLOBAL              2.26e+01 20 0.3106
plot(cox.zph(cox_men))

cox_women <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q) + AGEYRS + 
                        as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
            BMI + AVGSMK + as.factor(SIZE_CAT), data = d[d$SEX == 2, ])
summary(cox_women)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) + AGEYRS + 
##     as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
##     BMI + AVGSMK + as.factor(SIZE_CAT), data = d[d$SEX == 2, 
##     ])
## 
##   n= 4901, number of events= 887 
## 
##                                       coef  exp(coef)   se(coef)      z
## as.factor(BOOZE_q)0–0.5/week    -0.0334060  0.9671458  0.1087563 -0.307
## as.factor(BOOZE_q)0.5–2/week    -0.1735664  0.8406614  0.1050143 -1.653
## as.factor(BOOZE_q)>2/week       -0.0519451  0.9493809  0.1066823 -0.487
## AGEYRS                           0.0951472  1.0998207  0.0044638 21.315
## as.factor(RACE)2                 0.0581433  1.0598669  0.1180136  0.493
## as.factor(RACE)3                -0.0129767  0.9871071  0.3065457 -0.042
## as.factor(EDUC_CAT)Some HS      -0.0408000  0.9600211  0.0986586 -0.414
## as.factor(EDUC_CAT)HS Grad      -0.0325165  0.9680065  0.0885558 -0.367
## as.factor(EDUC_CAT)Some College -0.1861889  0.8301168  0.1308871 -1.423
## as.factor(EDUC_CAT)College+     -0.0707968  0.9316512  0.1386667 -0.511
## as.factor(MARRY)3                0.0633424  1.0653916  0.0780444  0.812
## as.factor(MARRY)4               -0.1531267  0.8580210  0.1626053 -0.942
## as.factor(MARRY)5                0.2341114  1.2637853  0.2382021  0.983
## as.factor(MARRY)6               -0.0202942  0.9799104  0.1557067 -0.130
## as.factor(MARRY)8               -0.0057576  0.9942590  0.5050423 -0.011
## BMI                             -0.0002604  0.9997396  0.0064150 -0.041
## AVGSMK                           0.0263737  1.0267246  0.0026682  9.884
## as.factor(SIZE_CAT)Small town    0.0279975  1.0283931  0.1050527  0.267
## as.factor(SIZE_CAT)Medium city  -0.0943020  0.9100079  0.1097958 -0.859
## as.factor(SIZE_CAT)Large city   -0.0142740  0.9858274  0.0849779 -0.168
##                                 Pr(>|z|)    
## as.factor(BOOZE_q)0–0.5/week      0.7587    
## as.factor(BOOZE_q)0.5–2/week      0.0984 .  
## as.factor(BOOZE_q)>2/week         0.6263    
## AGEYRS                            <2e-16 ***
## as.factor(RACE)2                  0.6222    
## as.factor(RACE)3                  0.9662    
## as.factor(EDUC_CAT)Some HS        0.6792    
## as.factor(EDUC_CAT)HS Grad        0.7135    
## as.factor(EDUC_CAT)Some College   0.1549    
## as.factor(EDUC_CAT)College+       0.6097    
## as.factor(MARRY)3                 0.4170    
## as.factor(MARRY)4                 0.3463    
## as.factor(MARRY)5                 0.3257    
## as.factor(MARRY)6                 0.8963    
## as.factor(MARRY)8                 0.9909    
## BMI                               0.9676    
## AVGSMK                            <2e-16 ***
## as.factor(SIZE_CAT)Small town     0.7898    
## as.factor(SIZE_CAT)Medium city    0.3904    
## as.factor(SIZE_CAT)Large city     0.8666    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week       0.9671     1.0340    0.7815     1.197
## as.factor(BOOZE_q)0.5–2/week       0.8407     1.1895    0.6843     1.033
## as.factor(BOOZE_q)>2/week          0.9494     1.0533    0.7703     1.170
## AGEYRS                             1.0998     0.9092    1.0902     1.109
## as.factor(RACE)2                   1.0599     0.9435    0.8410     1.336
## as.factor(RACE)3                   0.9871     1.0131    0.5413     1.800
## as.factor(EDUC_CAT)Some HS         0.9600     1.0416    0.7912     1.165
## as.factor(EDUC_CAT)HS Grad         0.9680     1.0331    0.8138     1.151
## as.factor(EDUC_CAT)Some College    0.8301     1.2046    0.6423     1.073
## as.factor(EDUC_CAT)College+        0.9317     1.0734    0.7099     1.223
## as.factor(MARRY)3                  1.0654     0.9386    0.9143     1.241
## as.factor(MARRY)4                  0.8580     1.1655    0.6239     1.180
## as.factor(MARRY)5                  1.2638     0.7913    0.7923     2.016
## as.factor(MARRY)6                  0.9799     1.0205    0.7222     1.330
## as.factor(MARRY)8                  0.9943     1.0058    0.3695     2.675
## BMI                                0.9997     1.0003    0.9872     1.012
## AVGSMK                             1.0267     0.9740    1.0214     1.032
## as.factor(SIZE_CAT)Small town      1.0284     0.9724    0.8370     1.264
## as.factor(SIZE_CAT)Medium city     0.9100     1.0989    0.7338     1.129
## as.factor(SIZE_CAT)Large city      0.9858     1.0144    0.8346     1.164
## 
## Concordance= 0.764  (se = 0.007 )
## Likelihood ratio test= 828.2  on 20 df,   p=<2e-16
## Wald test            = 582.2  on 20 df,   p=<2e-16
## Score (logrank) test = 687.7  on 20 df,   p=<2e-16
cox.zph(cox_women)
##                       chisq df     p
## as.factor(BOOZE_q)   5.9993  3 0.112
## AGEYRS               0.0715  1 0.789
## as.factor(RACE)      5.4630  2 0.065
## as.factor(EDUC_CAT)  6.1471  4 0.188
## as.factor(MARRY)     3.1200  5 0.681
## BMI                  3.1380  1 0.076
## AVGSMK               4.2504  1 0.039
## as.factor(SIZE_CAT)  2.8907  3 0.409
## GLOBAL              23.1428 20 0.282
plot(cox.zph(cox_women))

cox_men_lin <- coxph(Surv(FU, DEATH) ~ BOOZE + 
        AGEYRS + as.factor(RACE) +  as.factor(EDUC_CAT) + 
                    as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT), 
                    data = d[d$SEX == 1, ])
summary(cox_men_lin)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ BOOZE + AGEYRS + as.factor(RACE) + 
##     as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT), 
##     data = d[d$SEX == 1, ])
## 
##   n= 4349, number of events= 1258 
## 
##                                      coef exp(coef)  se(coef)      z Pr(>|z|)
## BOOZE                            0.004807  1.004819  0.004846  0.992  0.32118
## AGEYRS                           0.095153  1.099827  0.003579 26.589  < 2e-16
## as.factor(RACE)2                -0.110161  0.895690  0.098953 -1.113  0.26559
## as.factor(RACE)3                -0.515484  0.597211  0.262527 -1.964  0.04958
## as.factor(EDUC_CAT)Some HS       0.022980  1.023247  0.080324  0.286  0.77480
## as.factor(EDUC_CAT)HS Grad      -0.093860  0.910410  0.076414 -1.228  0.21933
## as.factor(EDUC_CAT)Some College -0.215128  0.806438  0.107099 -2.009  0.04457
## as.factor(EDUC_CAT)College+     -0.463280  0.629217  0.115535 -4.010 6.08e-05
## as.factor(MARRY)3                0.113628  1.120335  0.112818  1.007  0.31385
## as.factor(MARRY)4                0.399728  1.491419  0.130413  3.065  0.00218
## as.factor(MARRY)5                0.311784  1.365860  0.184113  1.693  0.09037
## as.factor(MARRY)6                0.339154  1.403760  0.125490  2.703  0.00688
## as.factor(MARRY)8                0.543790  1.722523  0.451993  1.203  0.22894
## BMI                             -0.018143  0.982020  0.007292 -2.488  0.01285
## AVGSMK                           0.019091  1.019275  0.001873 10.195  < 2e-16
## as.factor(SIZE_CAT)Small town    0.056321  1.057937  0.092803  0.607  0.54392
## as.factor(SIZE_CAT)Medium city   0.135716  1.145356  0.096188  1.411  0.15826
## as.factor(SIZE_CAT)Large city    0.009956  1.010006  0.069101  0.144  0.88544
##                                    
## BOOZE                              
## AGEYRS                          ***
## as.factor(RACE)2                   
## as.factor(RACE)3                *  
## as.factor(EDUC_CAT)Some HS         
## as.factor(EDUC_CAT)HS Grad         
## as.factor(EDUC_CAT)Some College *  
## as.factor(EDUC_CAT)College+     ***
## as.factor(MARRY)3                  
## as.factor(MARRY)4               ** 
## as.factor(MARRY)5               .  
## as.factor(MARRY)6               ** 
## as.factor(MARRY)8                  
## BMI                             *  
## AVGSMK                          ***
## as.factor(SIZE_CAT)Small town      
## as.factor(SIZE_CAT)Medium city     
## as.factor(SIZE_CAT)Large city      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## BOOZE                              1.0048     0.9952    0.9953    1.0144
## AGEYRS                             1.0998     0.9092    1.0921    1.1076
## as.factor(RACE)2                   0.8957     1.1165    0.7378    1.0874
## as.factor(RACE)3                   0.5972     1.6744    0.3570    0.9991
## as.factor(EDUC_CAT)Some HS         1.0232     0.9773    0.8742    1.1977
## as.factor(EDUC_CAT)HS Grad         0.9104     1.0984    0.7838    1.0575
## as.factor(EDUC_CAT)Some College    0.8064     1.2400    0.6537    0.9948
## as.factor(EDUC_CAT)College+        0.6292     1.5893    0.5017    0.7891
## as.factor(MARRY)3                  1.1203     0.8926    0.8981    1.3976
## as.factor(MARRY)4                  1.4914     0.6705    1.1550    1.9258
## as.factor(MARRY)5                  1.3659     0.7321    0.9521    1.9594
## as.factor(MARRY)6                  1.4038     0.7124    1.0977    1.7952
## as.factor(MARRY)8                  1.7225     0.5805    0.7103    4.1774
## BMI                                0.9820     1.0183    0.9681    0.9962
## AVGSMK                             1.0193     0.9811    1.0155    1.0230
## as.factor(SIZE_CAT)Small town      1.0579     0.9452    0.8820    1.2690
## as.factor(SIZE_CAT)Medium city     1.1454     0.8731    0.9486    1.3830
## as.factor(SIZE_CAT)Large city      1.0100     0.9901    0.8821    1.1565
## 
## Concordance= 0.775  (se = 0.006 )
## Likelihood ratio test= 1250  on 18 df,   p=<2e-16
## Wald test            = 875.8  on 18 df,   p=<2e-16
## Score (logrank) test = 1055  on 18 df,   p=<2e-16
#cox.zph(cox_men_lin)
#plot(cox.zph(cox_men_lin))

cox_women_lin <- coxph(Surv(FU, DEATH) ~ BOOZE + AGEYRS +
                        as.factor(RACE) + as.factor(EDUC_CAT) + as.factor(MARRY) + 
            BMI + AVGSMK + as.factor(SIZE_CAT), data = d[d$SEX == 2, ])
summary(cox_women_lin)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ BOOZE + AGEYRS + as.factor(RACE) + 
##     as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + AVGSMK + as.factor(SIZE_CAT), 
##     data = d[d$SEX == 2, ])
## 
##   n= 4901, number of events= 887 
## 
##                                       coef  exp(coef)   se(coef)      z
## BOOZE                           -0.0004860  0.9995141  0.0126942 -0.038
## AGEYRS                           0.0959040  1.1006534  0.0044463 21.570
## as.factor(RACE)2                 0.0695187  1.0719921  0.1177918  0.590
## as.factor(RACE)3                 0.0045725  1.0045830  0.3063751  0.015
## as.factor(EDUC_CAT)Some HS      -0.0467198  0.9543548  0.0985417 -0.474
## as.factor(EDUC_CAT)HS Grad      -0.0465275  0.9545383  0.0880187 -0.529
## as.factor(EDUC_CAT)Some College -0.2039894  0.8154710  0.1300834 -1.568
## as.factor(EDUC_CAT)College+     -0.0890168  0.9148302  0.1382296 -0.644
## as.factor(MARRY)3                0.0611352  1.0630426  0.0779948  0.784
## as.factor(MARRY)4               -0.1477257  0.8626677  0.1626036 -0.909
## as.factor(MARRY)5                0.2253535  1.2527655  0.2381139  0.946
## as.factor(MARRY)6               -0.0172190  0.9829284  0.1556646 -0.111
## as.factor(MARRY)8               -0.0303307  0.9701246  0.5046491 -0.060
## BMI                              0.0001807  1.0001807  0.0063993  0.028
## AVGSMK                           0.0262778  1.0266261  0.0026828  9.795
## as.factor(SIZE_CAT)Small town    0.0335570  1.0341264  0.1050501  0.319
## as.factor(SIZE_CAT)Medium city  -0.0791027  0.9239451  0.1092792 -0.724
## as.factor(SIZE_CAT)Large city    0.0076774  1.0077070  0.0838334  0.092
##                                 Pr(>|z|)    
## BOOZE                              0.969    
## AGEYRS                            <2e-16 ***
## as.factor(RACE)2                   0.555    
## as.factor(RACE)3                   0.988    
## as.factor(EDUC_CAT)Some HS         0.635    
## as.factor(EDUC_CAT)HS Grad         0.597    
## as.factor(EDUC_CAT)Some College    0.117    
## as.factor(EDUC_CAT)College+        0.520    
## as.factor(MARRY)3                  0.433    
## as.factor(MARRY)4                  0.364    
## as.factor(MARRY)5                  0.344    
## as.factor(MARRY)6                  0.912    
## as.factor(MARRY)8                  0.952    
## BMI                                0.977    
## AVGSMK                            <2e-16 ***
## as.factor(SIZE_CAT)Small town      0.749    
## as.factor(SIZE_CAT)Medium city     0.469    
## as.factor(SIZE_CAT)Large city      0.927    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                                 exp(coef) exp(-coef) lower .95 upper .95
## BOOZE                              0.9995     1.0005    0.9750     1.025
## AGEYRS                             1.1007     0.9086    1.0911     1.110
## as.factor(RACE)2                   1.0720     0.9328    0.8510     1.350
## as.factor(RACE)3                   1.0046     0.9954    0.5511     1.831
## as.factor(EDUC_CAT)Some HS         0.9544     1.0478    0.7867     1.158
## as.factor(EDUC_CAT)HS Grad         0.9545     1.0476    0.8033     1.134
## as.factor(EDUC_CAT)Some College    0.8155     1.2263    0.6319     1.052
## as.factor(EDUC_CAT)College+        0.9148     1.0931    0.6977     1.200
## as.factor(MARRY)3                  1.0630     0.9407    0.9123     1.239
## as.factor(MARRY)4                  0.8627     1.1592    0.6272     1.186
## as.factor(MARRY)5                  1.2528     0.7982    0.7856     1.998
## as.factor(MARRY)6                  0.9829     1.0174    0.7245     1.334
## as.factor(MARRY)8                  0.9701     1.0308    0.3608     2.608
## BMI                                1.0002     0.9998    0.9877     1.013
## AVGSMK                             1.0266     0.9741    1.0212     1.032
## as.factor(SIZE_CAT)Small town      1.0341     0.9670    0.8417     1.271
## as.factor(SIZE_CAT)Medium city     0.9239     1.0823    0.7458     1.145
## as.factor(SIZE_CAT)Large city      1.0077     0.9924    0.8550     1.188
## 
## Concordance= 0.763  (se = 0.007 )
## Likelihood ratio test= 825.3  on 18 df,   p=<2e-16
## Wald test            = 576.3  on 18 df,   p=<2e-16
## Score (logrank) test = 683  on 18 df,   p=<2e-16
#cox.zph(cox_women_lin)
#plot(cox.zph(cox_women_lin))

#Kaplan
fit<-survfit(Surv(FU, DEATH)~BOOZE_q, data=d)
summary(fit)
## Call: survfit(formula = Surv(FU, DEATH) ~ BOOZE_q, data = d)
## 
##                 BOOZE_q=0/week 
##     time n.risk n.event survival  std.err lower 95% CI upper 95% CI
##   0.0000   4053       2    1.000 0.000349        0.999        1.000
##   0.0833   4051       3    0.999 0.000551        0.998        1.000
##   0.1667   4048       1    0.999 0.000604        0.997        1.000
##   0.2500   4047       4    0.998 0.000779        0.996        0.999
##   0.3333   4043       6    0.996 0.000985        0.994        0.998
##   0.4167   4037       2    0.996 0.001044        0.994        0.998
##   0.5000   4035       2    0.995 0.001101        0.993        0.997
##   0.5833   4033       7    0.993 0.001278        0.991        0.996
##   0.6667   4026       3    0.993 0.001346        0.990        0.995
##   0.7500   4023       3    0.992 0.001412        0.989        0.995
##   0.8333   4020       4    0.991 0.001494        0.988        0.994
##   0.9167   4016       1    0.991 0.001514        0.988        0.994
##   1.0000   4015       6    0.989 0.001628        0.986        0.992
##   1.0833   4009       5    0.988 0.001717        0.985        0.991
##   1.1667   4004       5    0.987 0.001801        0.983        0.990
##   1.2500   3999       5    0.985 0.001881        0.982        0.989
##   1.3333   3994       4    0.984 0.001943        0.981        0.988
##   1.4167   3990       4    0.983 0.002003        0.980        0.987
##   1.5000   3986       6    0.982 0.002089        0.978        0.986
##   1.5833   3980       4    0.981 0.002144        0.977        0.985
##   1.6667   3976       6    0.980 0.002225        0.975        0.984
##   1.7500   3970      10    0.977 0.002352        0.972        0.982
##   1.8333   3960       7    0.975 0.002437        0.971        0.980
##   1.9167   3953       6    0.974 0.002507        0.969        0.979
##   2.0000   3947       4    0.973 0.002552        0.968        0.978
##   2.0833   3943       4    0.972 0.002597        0.967        0.977
##   2.1667   3939       1    0.972 0.002608        0.967        0.977
##   2.2500   3938       7    0.970 0.002684        0.965        0.975
##   2.3333   3931       3    0.969 0.002716        0.964        0.974
##   2.4167   3928       7    0.967 0.002788        0.962        0.973
##   2.5000   3921      11    0.965 0.002898        0.959        0.970
##   2.5833   3910       8    0.963 0.002975        0.957        0.969
##   2.6667   3902       8    0.961 0.003050        0.955        0.967
##   2.7500   3894       2    0.960 0.003068        0.954        0.966
##   2.8333   3892       2    0.960 0.003086        0.954        0.966
##   2.9167   3890       7    0.958 0.003149        0.952        0.964
##   3.0000   3883      10    0.956 0.003236        0.949        0.962
##   3.0833   3873       6    0.954 0.003287        0.948        0.961
##   3.1667   3867       5    0.953 0.003329        0.946        0.959
##   3.2500   3862       6    0.951 0.003378        0.945        0.958
##   3.3333   3856       1    0.951 0.003386        0.945        0.958
##   3.4167   3855       6    0.950 0.003434        0.943        0.956
##   3.5000   3849       1    0.949 0.003442        0.943        0.956
##   3.5833   3848       5    0.948 0.003482        0.941        0.955
##   3.6667   3843       8    0.946 0.003544        0.939        0.953
##   3.7500   3835      10    0.944 0.003619        0.937        0.951
##   3.8333   3825       1    0.943 0.003627        0.936        0.951
##   3.9167   3824       6    0.942 0.003671        0.935        0.949
##   4.0000   3818      10    0.940 0.003743        0.932        0.947
##   4.0833   3808       8    0.938 0.003800        0.930        0.945
##   4.1667   3800       1    0.937 0.003807        0.930        0.945
##   4.2500   3799       3    0.937 0.003828        0.929        0.944
##   4.3333   3796       5    0.935 0.003862        0.928        0.943
##   4.4167   3791       4    0.934 0.003890        0.927        0.942
##   4.5000   3787       4    0.933 0.003917        0.926        0.941
##   4.5833   3783       5    0.932 0.003950        0.924        0.940
##   4.6667   3778       7    0.930 0.003997        0.923        0.938
##   4.7500   3771       5    0.929 0.004029        0.921        0.937
##   4.8333   3766       7    0.927 0.004074        0.920        0.935
##   4.9167   3759       9    0.925 0.004131        0.917        0.933
##   5.0000   3750       4    0.924 0.004156        0.916        0.932
##   5.0833   3746       6    0.923 0.004193        0.915        0.931
##   5.1667   3740       7    0.921 0.004236        0.913        0.929
##   5.2500   3733       5    0.920 0.004266        0.911        0.928
##   5.3333   3728       5    0.919 0.004296        0.910        0.927
##   5.4167   3723       7    0.917 0.004337        0.908        0.925
##   5.5000   3716       8    0.915 0.004383        0.906        0.924
##   5.5833   3708       6    0.913 0.004418        0.905        0.922
##   5.6667   3702       9    0.911 0.004469        0.902        0.920
##   5.7500   3693       9    0.909 0.004519        0.900        0.918
##   5.8333   3684       9    0.907 0.004568        0.898        0.916
##   5.9167   3675       8    0.905 0.004611        0.896        0.914
##   6.0000   3667      10    0.902 0.004664        0.893        0.911
##   6.0833   3657       6    0.901 0.004695        0.892        0.910
##   6.1667   3651       4    0.900 0.004716        0.891        0.909
##   6.2500   3647       4    0.899 0.004736        0.890        0.908
##   6.3333   3643       6    0.897 0.004767        0.888        0.907
##   6.4167   3637       6    0.896 0.004797        0.887        0.905
##   6.5000   3631       4    0.895 0.004817        0.886        0.904
##   6.5833   3627       6    0.893 0.004847        0.884        0.903
##   6.6667   3621      10    0.891 0.004896        0.881        0.901
##   6.7500   3611       5    0.890 0.004920        0.880        0.899
##   6.8333   3606       9    0.887 0.004963        0.878        0.897
##   6.9167   3597       7    0.886 0.004997        0.876        0.896
##   7.0000   3590       4    0.885 0.005015        0.875        0.895
##   7.0833   3586       7    0.883 0.005048        0.873        0.893
##   7.1667   3579       7    0.881 0.005080        0.871        0.891
##   7.2500   3572       3    0.881 0.005094        0.871        0.891
##   7.3333   3569       7    0.879 0.005125        0.869        0.889
##   7.4167   3562       1    0.879 0.005130        0.869        0.889
##   7.5000   3561      11    0.876 0.005179        0.866        0.886
##   7.5833   3550       8    0.874 0.005214        0.864        0.884
##   7.6667   3542       9    0.872 0.005253        0.861        0.882
##   7.7500   3533       7    0.870 0.005283        0.860        0.880
##   7.8333   3526       6    0.868 0.005308        0.858        0.879
##   7.9167   3520      10    0.866 0.005350        0.856        0.877
##   8.0000   3510       7    0.864 0.005379        0.854        0.875
##   8.0833   3503       3    0.864 0.005392        0.853        0.874
##   8.1667   3500       8    0.862 0.005424        0.851        0.872
##   8.2500   3492       5    0.860 0.005445        0.850        0.871
##   8.3333   3487       5    0.859 0.005465        0.848        0.870
##   8.4167   3482       9    0.857 0.005500        0.846        0.868
##   8.5000   3473       7    0.855 0.005528        0.844        0.866
##   8.5833   3466       9    0.853 0.005563        0.842        0.864
##   8.6667   3457       6    0.851 0.005586        0.841        0.862
##   8.7500   3451       4    0.850 0.005601        0.840        0.862
##   8.8333   3447       4    0.849 0.005617        0.839        0.861
##   8.9167   3443       8    0.848 0.005647        0.837        0.859
##   9.0000   3435       6    0.846 0.005669        0.835        0.857
##   9.0833   3429       3    0.845 0.005680        0.834        0.857
##   9.1667   3426      10    0.843 0.005717        0.832        0.854
##   9.2500   3416       2    0.842 0.005724        0.831        0.854
##   9.3333   3414       4    0.841 0.005739        0.830        0.853
##   9.4167   3410       4    0.840 0.005753        0.829        0.852
##   9.5000   3406       4    0.839 0.005768        0.828        0.851
##   9.5833   3402       8    0.837 0.005796        0.826        0.849
##   9.6667   3394       8    0.835 0.005824        0.824        0.847
##   9.7500   3386       4    0.834 0.005838        0.823        0.846
##   9.8333   3382      10    0.832 0.005873        0.821        0.844
##   9.9167   3372       5    0.831 0.005890        0.819        0.842
##  10.0000   3367       8    0.829 0.005917        0.817        0.840
##  10.0833   3359       8    0.827 0.005944        0.815        0.839
##  10.1667   3351      11    0.824 0.005981        0.812        0.836
##  10.2500   3340       3    0.823 0.005991        0.812        0.835
##  10.3333   3337      10    0.821 0.006023        0.809        0.833
##  10.4167   3327       8    0.819 0.006049        0.807        0.831
##  10.5000   3319       6    0.817 0.006068        0.806        0.829
##  10.5833   3313       4    0.816 0.006081        0.805        0.828
##  10.6667   3309       7    0.815 0.006103        0.803        0.827
##  10.7500   3302       8    0.813 0.006128        0.801        0.825
##  10.8333   3294       5    0.811 0.006143        0.800        0.824
##  10.9167   3289       8    0.810 0.006168        0.798        0.822
##  11.0000   3281       6    0.808 0.006186        0.796        0.820
##  11.0833   3275       5    0.807 0.006201        0.795        0.819
##  11.1667   3270       6    0.805 0.006219        0.793        0.818
##  11.2500   3264       5    0.804 0.006234        0.792        0.816
##  11.3333   3259      12    0.801 0.006270        0.789        0.814
##  11.4167   3247       5    0.800 0.006284        0.788        0.812
##  11.5000   3242      10    0.797 0.006313        0.785        0.810
##  11.5833   3232       9    0.795 0.006339        0.783        0.808
##  11.6667   3223       9    0.793 0.006364        0.781        0.806
##  11.7500   3214       5    0.792 0.006378        0.779        0.804
##  11.8333   3209       5    0.791 0.006392        0.778        0.803
##  11.9167   3204       7    0.789 0.006411        0.776        0.801
##  12.0000   3197       6    0.787 0.006428        0.775        0.800
##  12.0833   3191       8    0.785 0.006449        0.773        0.798
##  12.1667   3183       7    0.784 0.006468        0.771        0.796
##  12.2500   3176       3    0.783 0.006476        0.770        0.796
##  12.3333   3173       9    0.781 0.006500        0.768        0.794
##  12.4167   3164       7    0.779 0.006518        0.766        0.792
##  12.5000   3157       9    0.777 0.006541        0.764        0.790
##  12.5833   3148       9    0.774 0.006565        0.762        0.787
##  12.6667   3139       3    0.774 0.006572        0.761        0.787
##  12.7500   3136       8    0.772 0.006592        0.759        0.785
##  12.8333   3128       6    0.770 0.006607        0.757        0.783
##  12.9167   3032       6    0.769 0.006624        0.756        0.782
##  13.0000   2965       9    0.766 0.006649        0.754        0.780
##  13.0833   2935       5    0.765 0.006663        0.752        0.778
##  13.1667   2849       4    0.764 0.006675        0.751        0.777
##  13.2500   2773       4    0.763 0.006689        0.750        0.776
##  13.3333   2688       6    0.761 0.006710        0.748        0.775
##  13.4167   2583       4    0.760 0.006725        0.747        0.773
##  13.5000   2578       6    0.758 0.006748        0.745        0.772
##  13.5833   2503       3    0.757 0.006760        0.744        0.771
##  13.6667   2438       7    0.755 0.006791        0.742        0.769
##  13.7500   2342       5    0.754 0.006814        0.740        0.767
##  13.8333   2194       5    0.752 0.006842        0.739        0.765
##  13.9167   2115       3    0.751 0.006860        0.737        0.764
##  14.0000   2062       1    0.750 0.006866        0.737        0.764
##  14.0833   2048       2    0.750 0.006879        0.736        0.763
##  14.1667   2009       1    0.749 0.006886        0.736        0.763
##  14.2500   1965       6    0.747 0.006928        0.734        0.761
##  14.3333   1926       6    0.745 0.006971        0.731        0.759
##  14.4167   1857       2    0.744 0.006987        0.730        0.758
##  14.5000   1806       6    0.741 0.007036        0.728        0.755
##  14.5833   1700       2    0.741 0.007055        0.727        0.755
##  14.6667   1617       4    0.739 0.007096        0.725        0.753
##  14.7500   1518       2    0.738 0.007120        0.724        0.752
##  14.8333   1456       2    0.737 0.007147        0.723        0.751
##  14.9167   1425       1    0.736 0.007160        0.722        0.750
##  15.0000   1397       4    0.734 0.007217        0.720        0.748
##  15.0833   1340       3    0.733 0.007263        0.718        0.747
##  15.1667   1291       2    0.731 0.007296        0.717        0.746
##  15.2500   1262       1    0.731 0.007313        0.717        0.745
##  15.3333   1228       5    0.728 0.007403        0.713        0.742
##  15.4167   1178       3    0.726 0.007461        0.711        0.741
##  15.5000   1145       2    0.725 0.007502        0.710        0.740
##  15.5833   1114       2    0.723 0.007545        0.709        0.738
##  15.6667   1079       2    0.722 0.007590        0.707        0.737
##  15.7500   1018       1    0.721 0.007616        0.707        0.736
##  15.8333    860       1    0.721 0.007653        0.706        0.736
##  15.9167    803       3    0.718 0.007781        0.703        0.733
##  16.0000    770       2    0.716 0.007871        0.701        0.732
##  16.0833    670       1    0.715 0.007932        0.699        0.731
##  16.2500    548       1    0.714 0.008024        0.698        0.729
##  16.3333    512       3    0.709 0.008332        0.693        0.726
##  16.5833    220       1    0.706 0.008896        0.689        0.724
## 
##                 BOOZE_q=0–0.5/week 
##     time n.risk n.event survival std.err lower 95% CI upper 95% CI
##   0.0000    941       1    0.999 0.00106        0.997        1.000
##   0.0833    940       2    0.997 0.00184        0.993        1.000
##   0.2500    938       1    0.996 0.00212        0.992        1.000
##   0.3333    937       1    0.995 0.00237        0.990        0.999
##   0.5000    936       1    0.994 0.00259        0.989        0.999
##   0.5833    935       2    0.991 0.00299        0.986        0.997
##   0.6667    933       1    0.990 0.00317        0.984        0.997
##   0.8333    932       1    0.989 0.00334        0.983        0.996
##   0.9167    931       1    0.988 0.00350        0.981        0.995
##   1.1667    930       2    0.986 0.00381        0.979        0.994
##   1.2500    928       1    0.985 0.00395        0.977        0.993
##   1.3333    927       1    0.984 0.00408        0.976        0.992
##   1.4167    926       1    0.983 0.00421        0.975        0.991
##   1.5000    925       2    0.981 0.00447        0.972        0.990
##   1.7500    923       2    0.979 0.00470        0.970        0.988
##   1.8333    921       1    0.978 0.00482        0.968        0.987
##   2.0000    920       1    0.977 0.00493        0.967        0.986
##   2.0833    919       1    0.976 0.00503        0.966        0.985
##   2.1667    918       1    0.974 0.00514        0.964        0.985
##   2.2500    917       2    0.972 0.00534        0.962        0.983
##   2.3333    915       1    0.971 0.00544        0.961        0.982
##   2.4167    914       1    0.970 0.00554        0.959        0.981
##   2.5000    913       1    0.969 0.00563        0.958        0.980
##   2.5833    912       1    0.968 0.00573        0.957        0.979
##   2.6667    911       2    0.966 0.00591        0.954        0.978
##   2.7500    909       2    0.964 0.00608        0.952        0.976
##   2.8333    907       2    0.962 0.00625        0.950        0.974
##   2.9167    905       1    0.961 0.00634        0.948        0.973
##   3.0000    904       1    0.960 0.00642        0.947        0.972
##   3.0833    903       1    0.959 0.00650        0.946        0.971
##   3.2500    902       3    0.955 0.00673        0.942        0.969
##   3.3333    899       2    0.953 0.00688        0.940        0.967
##   3.5000    897       1    0.952 0.00696        0.939        0.966
##   3.6667    896       2    0.950 0.00710        0.936        0.964
##   3.7500    894       3    0.947 0.00731        0.933        0.961
##   3.8333    891       1    0.946 0.00738        0.931        0.960
##   4.0000    890       1    0.945 0.00745        0.930        0.959
##   4.0833    889       1    0.944 0.00752        0.929        0.959
##   4.4167    888       1    0.943 0.00758        0.928        0.958
##   4.5000    887       1    0.942 0.00765        0.927        0.957
##   4.7500    886       3    0.938 0.00784        0.923        0.954
##   4.9167    883       1    0.937 0.00790        0.922        0.953
##   5.0000    882       1    0.936 0.00796        0.921        0.952
##   5.0833    881       2    0.934 0.00809        0.918        0.950
##   5.3333    879       2    0.932 0.00821        0.916        0.948
##   5.4167    877       1    0.931 0.00827        0.915        0.947
##   5.5833    876       1    0.930 0.00833        0.914        0.946
##   5.6667    875       1    0.929 0.00838        0.913        0.945
##   5.7500    874       2    0.927 0.00850        0.910        0.943
##   5.8333    872       1    0.926 0.00855        0.909        0.943
##   5.9167    871       1    0.925 0.00861        0.908        0.942
##   6.1667    870       4    0.920 0.00883        0.903        0.938
##   6.2500    866       1    0.919 0.00888        0.902        0.937
##   6.3333    865       2    0.917 0.00899        0.900        0.935
##   6.5000    863       1    0.916 0.00904        0.898        0.934
##   6.5833    862       3    0.913 0.00919        0.895        0.931
##   6.6667    859       1    0.912 0.00924        0.894        0.930
##   7.0833    858       1    0.911 0.00929        0.893        0.929
##   7.1667    857       1    0.910 0.00934        0.892        0.928
##   7.2500    856       1    0.909 0.00939        0.890        0.927
##   7.3333    855       2    0.906 0.00949        0.888        0.925
##   7.5000    853       2    0.904 0.00959        0.886        0.923
##   7.5833    851       2    0.902 0.00968        0.883        0.921
##   7.7500    849       1    0.901 0.00973        0.882        0.920
##   7.8333    848       1    0.900 0.00978        0.881        0.919
##   8.0000    847       2    0.898 0.00987        0.879        0.918
##   8.0833    845       2    0.896 0.00996        0.877        0.916
##   8.1667    843       2    0.894 0.01005        0.874        0.914
##   8.3333    841       1    0.893 0.01009        0.873        0.913
##   8.4167    840       1    0.892 0.01013        0.872        0.912
##   8.5000    839       2    0.889 0.01022        0.870        0.910
##   8.5833    837       1    0.888 0.01026        0.869        0.909
##   8.6667    836       3    0.885 0.01039        0.865        0.906
##   8.7500    833       2    0.883 0.01047        0.863        0.904
##   8.8333    831       2    0.881 0.01056        0.861        0.902
##   8.9167    829       1    0.880 0.01060        0.859        0.901
##   9.0000    828       3    0.877 0.01072        0.856        0.898
##   9.0833    825       1    0.876 0.01076        0.855        0.897
##   9.3333    824       1    0.875 0.01080        0.854        0.896
##   9.4167    823       1    0.874 0.01083        0.853        0.895
##   9.5833    822       2    0.871 0.01091        0.850        0.893
##   9.6667    820       3    0.868 0.01103        0.847        0.890
##   9.7500    817       3    0.865 0.01114        0.843        0.887
##   9.8333    814       1    0.864 0.01118        0.842        0.886
##  10.0833    813       1    0.863 0.01121        0.841        0.885
##  10.2500    812       4    0.859 0.01136        0.837        0.881
##  10.5833    808       2    0.857 0.01143        0.834        0.879
##  10.6667    806       2    0.854 0.01150        0.832        0.877
##  10.7500    804       2    0.852 0.01157        0.830        0.875
##  10.9167    802       3    0.849 0.01167        0.827        0.872
##  11.0000    799       2    0.847 0.01174        0.824        0.870
##  11.0833    797       1    0.846 0.01177        0.823        0.869
##  11.1667    796       1    0.845 0.01180        0.822        0.868
##  11.2500    795       2    0.843 0.01187        0.820        0.866
##  11.3333    793       1    0.842 0.01190        0.819        0.865
##  11.4167    792       2    0.840 0.01197        0.816        0.863
##  11.5000    790       2    0.837 0.01203        0.814        0.861
##  11.5833    788       3    0.834 0.01212        0.811        0.858
##  11.6667    785       1    0.833 0.01215        0.810        0.857
##  11.7500    784       1    0.832 0.01218        0.809        0.856
##  11.8333    783       1    0.831 0.01222        0.807        0.855
##  11.9167    782       2    0.829 0.01228        0.805        0.853
##  12.0000    780       1    0.828 0.01231        0.804        0.852
##  12.0833    779       1    0.827 0.01234        0.803        0.851
##  12.1667    778       3    0.824 0.01243        0.800        0.848
##  12.2500    775       2    0.821 0.01248        0.797        0.846
##  12.3333    773       1    0.820 0.01251        0.796        0.845
##  12.4167    772       1    0.819 0.01254        0.795        0.844
##  12.5000    771       1    0.818 0.01257        0.794        0.843
##  12.6667    770       3    0.815 0.01266        0.791        0.840
##  12.7500    767       1    0.814 0.01268        0.790        0.839
##  12.8333    766       1    0.813 0.01271        0.788        0.838
##  13.0833    738       1    0.812 0.01274        0.787        0.837
##  13.1667    718       3    0.808 0.01284        0.784        0.834
##  13.2500    697       1    0.807 0.01287        0.782        0.833
##  13.3333    668       2    0.805 0.01295        0.780        0.831
##  13.4167    642       2    0.802 0.01303        0.777        0.828
##  13.5000    639       1    0.801 0.01307        0.776        0.827
##  13.5833    613       2    0.799 0.01315        0.773        0.825
##  13.6667    591       3    0.794 0.01329        0.769        0.821
##  13.8333    556       2    0.792 0.01340        0.766        0.818
##  14.0000    522       1    0.790 0.01346        0.764        0.817
##  14.0833    515       2    0.787 0.01358        0.761        0.814
##  14.2500    482       5    0.779 0.01392        0.752        0.807
##  14.3333    471       1    0.777 0.01399        0.750        0.805
##  14.4167    442       1    0.775 0.01407        0.748        0.804
##  14.6667    390       2    0.771 0.01427        0.744        0.800
##  15.0000    329       1    0.769 0.01442        0.741        0.798
##  15.2500    283       1    0.766 0.01463        0.738        0.796
##  15.6667    219       1    0.763 0.01497        0.734        0.793
##  15.7500    197       1    0.759 0.01539        0.729        0.790
##  15.9167    173       1    0.755 0.01591        0.724        0.786
##  16.1667    141       1    0.749 0.01668        0.717        0.783
##  16.5833     57       1    0.736 0.02093        0.696        0.778
##  16.6667     45       1    0.720 0.02609        0.670        0.773
## 
##                 BOOZE_q=0.5–2/week 
##     time n.risk n.event survival  std.err lower 95% CI upper 95% CI
##   0.0000   1729       1    0.999 0.000578        0.998        1.000
##   0.0833   1728       1    0.999 0.000817        0.997        1.000
##   0.1667   1727       1    0.998 0.001001        0.996        1.000
##   0.3333   1726       1    0.998 0.001155        0.995        1.000
##   0.4167   1725       1    0.997 0.001291        0.995        1.000
##   0.7500   1724       1    0.997 0.001414        0.994        0.999
##   0.8333   1723       1    0.996 0.001527        0.993        0.999
##   1.0000   1722       3    0.994 0.001824        0.991        0.998
##   1.1667   1719       2    0.993 0.001997        0.989        0.997
##   1.2500   1717       3    0.991 0.002230        0.987        0.996
##   1.3333   1714       2    0.990 0.002373        0.986        0.995
##   1.4167   1712       1    0.990 0.002441        0.985        0.994
##   1.5000   1711       1    0.989 0.002507        0.984        0.994
##   1.5833   1710       1    0.988 0.002572        0.983        0.993
##   1.6667   1709       2    0.987 0.002695        0.982        0.993
##   1.7500   1707       2    0.986 0.002814        0.981        0.992
##   1.8333   1705       1    0.986 0.002871        0.980        0.991
##   2.0000   1704       1    0.985 0.002927        0.979        0.991
##   2.0833   1703       2    0.984 0.003036        0.978        0.990
##   2.1667   1701       1    0.983 0.003088        0.977        0.989
##   2.2500   1700       1    0.983 0.003140        0.977        0.989
##   2.3333   1699       1    0.982 0.003191        0.976        0.988
##   2.5000   1698       4    0.980 0.003387        0.973        0.986
##   2.5833   1694       2    0.979 0.003480        0.972        0.985
##   2.6667   1692       2    0.977 0.003571        0.970        0.984
##   2.7500   1690       3    0.976 0.003702        0.968        0.983
##   2.8333   1687       3    0.974 0.003829        0.966        0.982
##   2.9167   1684       4    0.972 0.003991        0.964        0.980
##   3.0000   1680       1    0.971 0.004030        0.963        0.979
##   3.0833   1679       2    0.970 0.004107        0.962        0.978
##   3.1667   1677       2    0.969 0.004183        0.961        0.977
##   3.2500   1675       1    0.968 0.004221        0.960        0.976
##   3.3333   1674       2    0.967 0.004294        0.959        0.975
##   3.4167   1672       2    0.966 0.004366        0.957        0.974
##   3.5000   1670       1    0.965 0.004402        0.957        0.974
##   3.5833   1669       2    0.964 0.004472        0.955        0.973
##   3.6667   1667       3    0.962 0.004574        0.953        0.971
##   3.7500   1664       1    0.962 0.004608        0.953        0.971
##   3.8333   1663       3    0.960 0.004707        0.951        0.969
##   4.0000   1660       5    0.957 0.004868        0.948        0.967
##   4.0833   1655       3    0.955 0.004961        0.946        0.965
##   4.1667   1652       4    0.953 0.005082        0.943        0.963
##   4.2500   1648       1    0.953 0.005112        0.943        0.963
##   4.3333   1647       2    0.951 0.005170        0.941        0.962
##   4.4167   1645       1    0.951 0.005200        0.941        0.961
##   4.5000   1644       1    0.950 0.005228        0.940        0.961
##   4.5833   1643       1    0.950 0.005257        0.939        0.960
##   4.6667   1642       2    0.949 0.005314        0.938        0.959
##   4.7500   1640       2    0.947 0.005370        0.937        0.958
##   4.8333   1638       1    0.947 0.005398        0.936        0.957
##   4.9167   1637       2    0.946 0.005453        0.935        0.956
##   5.0000   1635       2    0.944 0.005507        0.934        0.955
##   5.0833   1633       4    0.942 0.005614        0.931        0.953
##   5.2500   1629       2    0.941 0.005666        0.930        0.952
##   5.4167   1627       2    0.940 0.005718        0.929        0.951
##   5.5000   1625       1    0.939 0.005744        0.928        0.951
##   5.5833   1624       1    0.939 0.005769        0.927        0.950
##   5.6667   1623       1    0.938 0.005795        0.927        0.950
##   5.7500   1622       2    0.937 0.005845        0.926        0.948
##   5.8333   1620       1    0.936 0.005870        0.925        0.948
##   6.0833   1619       2    0.935 0.005919        0.924        0.947
##   6.1667   1617       1    0.935 0.005944        0.923        0.946
##   6.2500   1616       1    0.934 0.005968        0.922        0.946
##   6.4167   1615       3    0.932 0.006041        0.921        0.944
##   6.5000   1612       1    0.932 0.006065        0.920        0.944
##   6.5833   1611       4    0.929 0.006159        0.917        0.942
##   6.6667   1607       3    0.928 0.006228        0.916        0.940
##   6.7500   1604       4    0.925 0.006319        0.913        0.938
##   6.8333   1600       1    0.925 0.006342        0.912        0.937
##   6.9167   1599       1    0.924 0.006364        0.912        0.937
##   7.0000   1598       1    0.924 0.006386        0.911        0.936
##   7.0833   1597       1    0.923 0.006408        0.911        0.936
##   7.1667   1596       1    0.922 0.006430        0.910        0.935
##   7.2500   1595       1    0.922 0.006452        0.909        0.935
##   7.3333   1594       4    0.920 0.006539        0.907        0.933
##   7.4167   1590       1    0.919 0.006560        0.906        0.932
##   7.5000   1589       1    0.918 0.006582        0.906        0.931
##   7.5833   1588       5    0.916 0.006687        0.903        0.929
##   7.6667   1583       6    0.912 0.006810        0.899        0.926
##   7.7500   1577       1    0.912 0.006830        0.898        0.925
##   7.8333   1576       1    0.911 0.006850        0.898        0.924
##   7.9167   1575       1    0.910 0.006870        0.897        0.924
##   8.0000   1574       3    0.909 0.006930        0.895        0.922
##   8.0833   1571       3    0.907 0.006989        0.893        0.921
##   8.1667   1568       4    0.905 0.007066        0.891        0.919
##   8.2500   1564       3    0.903 0.007123        0.889        0.917
##   8.3333   1561       3    0.901 0.007179        0.887        0.915
##   8.4167   1558       2    0.900 0.007217        0.886        0.914
##   8.5000   1556       3    0.898 0.007272        0.884        0.913
##   8.5833   1553       1    0.898 0.007290        0.883        0.912
##   8.6667   1552       1    0.897 0.007308        0.883        0.911
##   8.7500   1551       3    0.895 0.007363        0.881        0.910
##   8.8333   1548       1    0.895 0.007381        0.880        0.909
##   8.9167   1547       2    0.894 0.007416        0.879        0.908
##   9.0000   1545       1    0.893 0.007434        0.879        0.908
##   9.1667   1544       3    0.891 0.007487        0.877        0.906
##   9.4167   1541       1    0.891 0.007504        0.876        0.906
##   9.5000   1540       1    0.890 0.007521        0.875        0.905
##   9.5833   1539       3    0.888 0.007573        0.874        0.903
##   9.6667   1536       1    0.888 0.007590        0.873        0.903
##   9.7500   1535       2    0.887 0.007624        0.872        0.902
##   9.8333   1533       2    0.885 0.007658        0.871        0.901
##   9.9167   1531       2    0.884 0.007692        0.869        0.900
##  10.0000   1529       1    0.884 0.007708        0.869        0.899
##  10.0833   1528       3    0.882 0.007758        0.867        0.897
##  10.1667   1525       3    0.880 0.007807        0.865        0.896
##  10.2500   1522       2    0.879 0.007840        0.864        0.895
##  10.3333   1520       1    0.879 0.007856        0.863        0.894
##  10.4167   1519       4    0.876 0.007920        0.861        0.892
##  10.5000   1515       3    0.874 0.007967        0.859        0.890
##  10.5833   1512       5    0.872 0.008045        0.856        0.888
##  10.6667   1507       1    0.871 0.008061        0.855        0.887
##  10.7500   1506       1    0.870 0.008076        0.855        0.886
##  10.8333   1505       2    0.869 0.008107        0.854        0.885
##  10.9167   1503       2    0.868 0.008137        0.852        0.884
##  11.0000   1501       2    0.867 0.008167        0.851        0.883
##  11.1667   1499       1    0.866 0.008182        0.851        0.883
##  11.2500   1498       2    0.865 0.008212        0.849        0.881
##  11.3333   1496       2    0.864 0.008242        0.848        0.880
##  11.4167   1494       1    0.864 0.008256        0.847        0.880
##  11.5000   1493       3    0.862 0.008300        0.846        0.878
##  11.5833   1490       3    0.860 0.008344        0.844        0.877
##  11.6667   1487       2    0.859 0.008373        0.843        0.875
##  11.7500   1485       2    0.858 0.008401        0.841        0.874
##  11.8333   1483       3    0.856 0.008444        0.840        0.873
##  11.9167   1480       2    0.855 0.008472        0.838        0.872
##  12.0000   1478       2    0.854 0.008500        0.837        0.870
##  12.1667   1476       4    0.851 0.008555        0.835        0.868
##  12.2500   1472       3    0.850 0.008596        0.833        0.867
##  12.3333   1469       3    0.848 0.008637        0.831        0.865
##  12.4167   1466       3    0.846 0.008677        0.829        0.863
##  12.5000   1463       1    0.846 0.008690        0.829        0.863
##  12.6667   1462       2    0.844 0.008717        0.828        0.862
##  12.7500   1460       5    0.842 0.008782        0.824        0.859
##  12.8333   1455       2    0.840 0.008808        0.823        0.858
##  12.9167   1425       3    0.839 0.008849        0.821        0.856
##  13.0000   1403       1    0.838 0.008863        0.821        0.856
##  13.0833   1393       1    0.837 0.008877        0.820        0.855
##  13.1667   1364       4    0.835 0.008935        0.818        0.853
##  13.2500   1330       4    0.832 0.008996        0.815        0.850
##  13.3333   1287       2    0.831 0.009029        0.814        0.849
##  13.5000   1230       1    0.830 0.009046        0.813        0.848
##  13.5833   1182       1    0.830 0.009066        0.812        0.848
##  13.6667   1156       2    0.828 0.009107        0.811        0.846
##  13.7500   1119       2    0.827 0.009151        0.809        0.845
##  13.8333   1086       1    0.826 0.009174        0.808        0.844
##  13.9167   1071       1    0.825 0.009198        0.807        0.844
##  14.0833   1037       1    0.825 0.009223        0.807        0.843
##  14.1667    999       2    0.823 0.009278        0.805        0.841
##  14.2500    955       1    0.822 0.009308        0.804        0.840
##  14.3333    931       3    0.819 0.009403        0.801        0.838
##  14.4167    879       2    0.817 0.009474        0.799        0.836
##  14.5000    815       1    0.816 0.009515        0.798        0.835
##  14.9167    676       2    0.814 0.009639        0.795        0.833
##  15.0000    660       2    0.812 0.009766        0.793        0.831
##  15.0833    647       2    0.809 0.009896        0.790        0.829
##  15.1667    628       3    0.805 0.010097        0.786        0.825
##  15.5000    498       3    0.800 0.010418        0.780        0.821
##  15.5833    463       3    0.795 0.010772        0.774        0.817
##  15.9167    340       1    0.793 0.010991        0.772        0.815
## 
##                 BOOZE_q=>2/week 
##    time n.risk n.event survival  std.err lower 95% CI upper 95% CI
##   0.167   2527       4    0.998 0.000791        0.997        1.000
##   0.250   2523       1    0.998 0.000884        0.996        1.000
##   0.333   2522       4    0.996 0.001185        0.994        0.999
##   0.417   2518       1    0.996 0.001249        0.994        0.998
##   0.500   2517       4    0.994 0.001477        0.992        0.997
##   0.583   2513       1    0.994 0.001528        0.991        0.997
##   0.750   2512       1    0.994 0.001578        0.991        0.997
##   0.833   2511       3    0.992 0.001718        0.989        0.996
##   0.917   2508       1    0.992 0.001763        0.989        0.996
##   1.000   2507       2    0.991 0.001848        0.988        0.995
##   1.083   2505       4    0.990 0.002007        0.986        0.994
##   1.167   2501       2    0.989 0.002082        0.985        0.993
##   1.250   2499       1    0.989 0.002119        0.984        0.993
##   1.333   2498       3    0.987 0.002224        0.983        0.992
##   1.417   2495       1    0.987 0.002258        0.983        0.991
##   1.500   2494       3    0.986 0.002357        0.981        0.990
##   1.583   2491       1    0.985 0.002389        0.981        0.990
##   1.750   2490       1    0.985 0.002421        0.980        0.990
##   1.833   2489       2    0.984 0.002483        0.979        0.989
##   2.000   2487       1    0.984 0.002513        0.979        0.989
##   2.083   2486       1    0.983 0.002543        0.978        0.988
##   2.167   2485       1    0.983 0.002573        0.978        0.988
##   2.250   2484       1    0.983 0.002602        0.978        0.988
##   2.333   2483       1    0.982 0.002631        0.977        0.987
##   2.417   2482       1    0.982 0.002659        0.977        0.987
##   2.500   2481       4    0.980 0.002770        0.975        0.986
##   2.583   2477       2    0.979 0.002824        0.974        0.985
##   2.667   2475       1    0.979 0.002851        0.973        0.985
##   2.833   2474       3    0.978 0.002928        0.972        0.984
##   2.917   2471       3    0.977 0.003004        0.971        0.983
##   3.000   2468       6    0.974 0.003149        0.968        0.980
##   3.083   2462       3    0.973 0.003219        0.967        0.979
##   3.167   2459       1    0.973 0.003242        0.966        0.979
##   3.250   2458       3    0.972 0.003310        0.965        0.978
##   3.333   2455       2    0.971 0.003354        0.964        0.977
##   3.417   2453       1    0.970 0.003376        0.964        0.977
##   3.500   2452       3    0.969 0.003441        0.962        0.976
##   3.583   2449       3    0.968 0.003504        0.961        0.975
##   3.667   2446       2    0.967 0.003546        0.960        0.974
##   3.750   2444       1    0.967 0.003566        0.960        0.974
##   3.833   2443       3    0.966 0.003627        0.958        0.973
##   3.917   2440       2    0.965 0.003667        0.958        0.972
##   4.000   2438       4    0.963 0.003745        0.956        0.971
##   4.250   2434       1    0.963 0.003765        0.955        0.970
##   4.333   2433       1    0.962 0.003784        0.955        0.970
##   4.417   2432       2    0.962 0.003822        0.954        0.969
##   4.500   2430       3    0.960 0.003878        0.953        0.968
##   4.583   2427       2    0.960 0.003915        0.952        0.967
##   4.667   2425       4    0.958 0.003988        0.950        0.966
##   4.750   2421       4    0.956 0.004059        0.949        0.964
##   4.833   2417       3    0.955 0.004111        0.947        0.963
##   4.917   2414       2    0.954 0.004146        0.946        0.963
##   5.000   2412       4    0.953 0.004214        0.945        0.961
##   5.083   2408       6    0.951 0.004314        0.942        0.959
##   5.167   2402       1    0.950 0.004330        0.942        0.959
##   5.250   2401       4    0.949 0.004394        0.940        0.957
##   5.333   2397       1    0.948 0.004410        0.940        0.957
##   5.417   2396       4    0.947 0.004473        0.938        0.955
##   5.500   2392       2    0.946 0.004505        0.937        0.955
##   5.583   2390       3    0.945 0.004551        0.936        0.954
##   5.667   2387       3    0.943 0.004596        0.934        0.952
##   5.750   2384       7    0.941 0.004701        0.931        0.950
##   5.833   2377       5    0.939 0.004773        0.929        0.948
##   5.917   2372       4    0.937 0.004830        0.928        0.947
##   6.000   2368       1    0.937 0.004845        0.927        0.946
##   6.167   2367       2    0.936 0.004873        0.926        0.945
##   6.250   2365       2    0.935 0.004901        0.926        0.945
##   6.333   2363       5    0.933 0.004969        0.923        0.943
##   6.417   2358       2    0.932 0.004997        0.923        0.942
##   6.583   2356       3    0.931 0.005037        0.921        0.941
##   6.667   2353       8    0.928 0.005143        0.918        0.938
##   6.750   2345       2    0.927 0.005169        0.917        0.937
##   6.833   2343       1    0.927 0.005182        0.917        0.937
##   6.917   2342       1    0.926 0.005195        0.916        0.937
##   7.000   2341       4    0.925 0.005246        0.915        0.935
##   7.083   2337       2    0.924 0.005271        0.914        0.934
##   7.167   2335       5    0.922 0.005333        0.912        0.933
##   7.250   2330       4    0.920 0.005383        0.910        0.931
##   7.333   2326       4    0.919 0.005431        0.908        0.930
##   7.417   2322       3    0.918 0.005467        0.907        0.928
##   7.500   2319       3    0.917 0.005503        0.906        0.927
##   7.583   2316       7    0.914 0.005585        0.903        0.925
##   7.667   2309       7    0.911 0.005665        0.900        0.922
##   7.750   2302       2    0.910 0.005688        0.899        0.921
##   7.833   2300       3    0.909 0.005722        0.898        0.920
##   8.000   2297       3    0.908 0.005755        0.897        0.919
##   8.083   2294       3    0.907 0.005788        0.895        0.918
##   8.167   2291       2    0.906 0.005810        0.895        0.917
##   8.250   2289       1    0.905 0.005821        0.894        0.917
##   8.333   2288       4    0.904 0.005865        0.892        0.915
##   8.417   2284       4    0.902 0.005908        0.891        0.914
##   8.500   2280       7    0.899 0.005981        0.888        0.911
##   8.583   2273       2    0.899 0.006002        0.887        0.911
##   8.667   2271       5    0.897 0.006054        0.885        0.909
##   8.750   2266       4    0.895 0.006095        0.883        0.907
##   8.833   2262       6    0.893 0.006155        0.881        0.905
##   8.917   2256       5    0.891 0.006205        0.879        0.903
##   9.000   2251       5    0.889 0.006254        0.877        0.901
##   9.083   2246       4    0.887 0.006293        0.875        0.900
##   9.167   2242       4    0.886 0.006331        0.873        0.898
##   9.250   2238       2    0.885 0.006350        0.872        0.897
##   9.333   2236       2    0.884 0.006369        0.872        0.897
##   9.417   2234       4    0.882 0.006407        0.870        0.895
##   9.500   2230       4    0.881 0.006444        0.868        0.894
##   9.583   2226       6    0.879 0.006499        0.866        0.891
##   9.667   2220       3    0.877 0.006526        0.865        0.890
##   9.750   2217       3    0.876 0.006553        0.863        0.889
##   9.833   2214       3    0.875 0.006580        0.862        0.888
##   9.917   2211       1    0.875 0.006589        0.862        0.888
##  10.000   2210       2    0.874 0.006607        0.861        0.887
##  10.083   2208       5    0.872 0.006651        0.859        0.885
##  10.167   2203       5    0.870 0.006694        0.857        0.883
##  10.250   2198       2    0.869 0.006712        0.856        0.882
##  10.333   2196       3    0.868 0.006737        0.855        0.881
##  10.417   2193       7    0.865 0.006797        0.852        0.878
##  10.500   2186       3    0.864 0.006822        0.851        0.877
##  10.583   2183       1    0.863 0.006830        0.850        0.877
##  10.667   2182       6    0.861 0.006880        0.848        0.875
##  10.750   2176       3    0.860 0.006904        0.846        0.874
##  10.833   2173       2    0.859 0.006921        0.846        0.873
##  10.917   2171       5    0.857 0.006961        0.844        0.871
##  11.000   2166       6    0.855 0.007009        0.841        0.869
##  11.083   2160       4    0.853 0.007040        0.839        0.867
##  11.167   2156       1    0.853 0.007048        0.839        0.867
##  11.250   2155       3    0.852 0.007072        0.838        0.866
##  11.333   2152       2    0.851 0.007087        0.837        0.865
##  11.417   2150       3    0.850 0.007110        0.836        0.864
##  11.500   2147       3    0.848 0.007134        0.835        0.863
##  11.583   2144       3    0.847 0.007156        0.833        0.861
##  11.667   2141       6    0.845 0.007202        0.831        0.859
##  11.750   2135       4    0.843 0.007232        0.829        0.858
##  11.833   2131       2    0.843 0.007246        0.828        0.857
##  11.917   2129       1    0.842 0.007254        0.828        0.856
##  12.000   2128       1    0.842 0.007261        0.828        0.856
##  12.083   2127       2    0.841 0.007276        0.827        0.855
##  12.167   2125       5    0.839 0.007312        0.825        0.853
##  12.250   2120       4    0.837 0.007341        0.823        0.852
##  12.333   2116       3    0.836 0.007363        0.822        0.851
##  12.417   2113       8    0.833 0.007419        0.819        0.848
##  12.500   2105       3    0.832 0.007441        0.817        0.847
##  12.583   2102       2    0.831 0.007454        0.817        0.846
##  12.667   2100       5    0.829 0.007489        0.814        0.844
##  12.750   2095       1    0.829 0.007496        0.814        0.843
##  12.833   2094       4    0.827 0.007523        0.812        0.842
##  12.917   2060       2    0.826 0.007537        0.812        0.841
##  13.000   2045       3    0.825 0.007559        0.810        0.840
##  13.083   2032       4    0.823 0.007587        0.809        0.838
##  13.167   1988       5    0.821 0.007625        0.807        0.836
##  13.250   1948       2    0.821 0.007640        0.806        0.836
##  13.333   1886       6    0.818 0.007690        0.803        0.833
##  13.417   1804       7    0.815 0.007753        0.800        0.830
##  13.500   1794       3    0.813 0.007780        0.798        0.829
##  13.583   1720       2    0.812 0.007799        0.797        0.828
##  13.667   1681       5    0.810 0.007851        0.795        0.826
##  13.750   1646       4    0.808 0.007893        0.793        0.824
##  13.833   1612       4    0.806 0.007937        0.791        0.822
##  13.917   1589       3    0.805 0.007970        0.789        0.820
##  14.000   1565       1    0.804 0.007982        0.789        0.820
##  14.083   1538       1    0.803 0.007994        0.788        0.819
##  14.167   1464       2    0.802 0.008020        0.787        0.818
##  14.250   1414       3    0.801 0.008063        0.785        0.817
##  14.333   1387       1    0.800 0.008078        0.784        0.816
##  14.417   1328       2    0.799 0.008111        0.783        0.815
##  14.500   1260       5    0.796 0.008202        0.780        0.812
##  14.583   1220       2    0.794 0.008240        0.778        0.811
##  14.667   1188       1    0.794 0.008260        0.778        0.810
##  14.750   1115       4    0.791 0.008352        0.775        0.807
##  14.833   1041       1    0.790 0.008379        0.774        0.807
##  14.917   1001       1    0.789 0.008407        0.773        0.806
##  15.000    963       2    0.788 0.008469        0.771        0.804
##  15.333    808       2    0.786 0.008560        0.769        0.803
##  15.417    755       3    0.783 0.008714        0.766        0.800
##  15.583    614       3    0.779 0.008946        0.761        0.797
##  15.667    589       1    0.777 0.009028        0.760        0.795
##  15.750    548       1    0.776 0.009123        0.758        0.794
##  15.833    530       2    0.773 0.009320        0.755        0.792
##  15.917    492       1    0.772 0.009433        0.753        0.790
##  16.000    460       1    0.770 0.009560        0.751        0.789
##  16.083    441       1    0.768 0.009697        0.749        0.787
##  16.167    422       1    0.766 0.009843        0.747        0.786
##  16.250    362       3    0.760 0.010422        0.740        0.781
##  16.417    225       1    0.757 0.010910        0.736        0.778
##  16.500    187       2    0.749 0.012201        0.725        0.773
##  16.583    169       1    0.744 0.012908        0.719        0.770
##  16.750     82       1    0.735 0.015618        0.705        0.766
summary(fit)$table
##                    records n.max n.start events    rmean  se(rmean) median
## BOOZE_q=0/week        4053  4053    4053   1070 14.42166 0.07071389     NA
## BOOZE_q=0–0.5/week     941   941     941    213 14.83118 0.13643836     NA
## BOOZE_q=0.5–2/week    1729  1729    1729    325 15.15602 0.09331554     NA
## BOOZE_q=>2/week       2527  2527    2527    537 15.03836 0.07729027     NA
##                    0.95LCL 0.95UCL
## BOOZE_q=0/week          NA      NA
## BOOZE_q=0–0.5/week      NA      NA
## BOOZE_q=0.5–2/week      NA      NA
## BOOZE_q=>2/week         NA      NA
#Log-rank test
survdiff(Surv(FU, DEATH)~BOOZE_q, data=d) 
## Call:
## survdiff(formula = Surv(FU, DEATH) ~ BOOZE_q, data = d)
## 
##                       N Observed Expected (O-E)^2/E (O-E)^2/V
## BOOZE_q=0/week     4053     1070      916    25.873    45.243
## BOOZE_q=0–0.5/week  941      213      219     0.139     0.155
## BOOZE_q=0.5–2/week 1729      325      411    18.013    22.319
## BOOZE_q=>2/week    2527      537      599     6.493     9.027
## 
##  Chisq= 50.6  on 3 degrees of freedom, p= 6e-11
#Sensitivity analysis (Poisson model)
#Exclude follow-up = 0
d_pois <- d %>%
  filter(FU > 0)

poisson <- glm(DEATH ~ as.factor(BOOZE_q) + SEX +
                 as.factor(RACE) + as.factor(EDUC_CAT) +
                 as.factor(MARRY) + BMI + AVGSMK + SIZE,
               family = poisson(link = "log"),
               offset = log(FU), data = d_pois)

summary(poisson)
## 
## Call:
## glm(formula = DEATH ~ as.factor(BOOZE_q) + SEX + as.factor(RACE) + 
##     as.factor(EDUC_CAT) + as.factor(MARRY) + BMI + AVGSMK + SIZE, 
##     family = poisson(link = "log"), data = d_pois, offset = log(FU))
## 
## Coefficients:
##                                  Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                     -2.062977   0.158501 -13.016  < 2e-16 ***
## as.factor(BOOZE_q)0–0.5/week    -0.134545   0.075929  -1.772 0.076396 .  
## as.factor(BOOZE_q)0.5–2/week    -0.385969   0.065539  -5.889 3.88e-09 ***
## as.factor(BOOZE_q)>2/week       -0.330099   0.058374  -5.655 1.56e-08 ***
## SEX                             -0.753542   0.048917 -15.404  < 2e-16 ***
## as.factor(RACE)2                -0.248327   0.074381  -3.339 0.000842 ***
## as.factor(RACE)3                -0.569211   0.202344  -2.813 0.004907 ** 
## as.factor(EDUC_CAT)Some HS      -0.234804   0.061827  -3.798 0.000146 ***
## as.factor(EDUC_CAT)HS Grad      -0.520908   0.056631  -9.198  < 2e-16 ***
## as.factor(EDUC_CAT)Some College -0.657512   0.082491  -7.971 1.58e-15 ***
## as.factor(EDUC_CAT)College+     -0.852910   0.088854  -9.599  < 2e-16 ***
## as.factor(MARRY)3                0.684032   0.061927  11.046  < 2e-16 ***
## as.factor(MARRY)4                0.044207   0.102176   0.433 0.665268    
## as.factor(MARRY)5                0.047057   0.144526   0.326 0.744732    
## as.factor(MARRY)6                0.157825   0.096299   1.639 0.101232    
## as.factor(MARRY)8                0.756500   0.335993   2.252 0.024352 *  
## BMI                             -0.013210   0.004669  -2.829 0.004663 ** 
## AVGSMK                           0.004975   0.001627   3.058 0.002225 ** 
## SIZE                            -0.023602   0.008487  -2.781 0.005422 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 9335.0  on 9245  degrees of freedom
## Residual deviance: 8739.6  on 9227  degrees of freedom
## AIC: 13060
## 
## Number of Fisher Scoring iterations: 6
exp(coef(poisson))
##                     (Intercept)    as.factor(BOOZE_q)0–0.5/week 
##                       0.1270752                       0.8741136 
##    as.factor(BOOZE_q)0.5–2/week       as.factor(BOOZE_q)>2/week 
##                       0.6797914                       0.7188525 
##                             SEX                as.factor(RACE)2 
##                       0.4706965                       0.7801048 
##                as.factor(RACE)3      as.factor(EDUC_CAT)Some HS 
##                       0.5659720                       0.7907257 
##      as.factor(EDUC_CAT)HS Grad as.factor(EDUC_CAT)Some College 
##                       0.5939810                       0.5181391 
##     as.factor(EDUC_CAT)College+               as.factor(MARRY)3 
##                       0.4261731                       1.9818516 
##               as.factor(MARRY)4               as.factor(MARRY)5 
##                       1.0451982                       1.0481816 
##               as.factor(MARRY)6               as.factor(MARRY)8 
##                       1.1709608                       2.1308046 
##                             BMI                          AVGSMK 
##                       0.9868769                       1.0049872 
##                            SIZE 
##                       0.9766748
exp(confint(poisson))
## Waiting for profiling to be done...
##                                     2.5 %    97.5 %
## (Intercept)                     0.0931873 0.1734571
## as.factor(BOOZE_q)0–0.5/week    0.7513986 1.0120424
## as.factor(BOOZE_q)0.5–2/week    0.5970498 0.7720081
## as.factor(BOOZE_q)>2/week       0.6408378 0.8056426
## SEX                             0.4275597 0.5179443
## as.factor(RACE)2                0.6727843 0.9006519
## as.factor(RACE)3                0.3706034 0.8219676
## as.factor(EDUC_CAT)Some HS      0.6999102 0.8919260
## as.factor(EDUC_CAT)HS Grad      0.5314196 0.6635397
## as.factor(EDUC_CAT)Some College 0.4396896 0.6076562
## as.factor(EDUC_CAT)College+     0.3570011 0.5058604
## as.factor(MARRY)3               1.7535386 2.2354530
## as.factor(MARRY)4               0.8506068 1.2701349
## as.factor(MARRY)5               0.7802367 1.3764588
## as.factor(MARRY)6               0.9646147 1.4074806
## as.factor(MARRY)8               1.0195924 3.8653838
## BMI                             0.9778251 0.9958847
## AVGSMK                          1.0017430 1.0081514
## SIZE                            0.9605928 0.9930919
#Table 2
# Age-adjusted Cox model
cox_age <- coxph(Surv(FU, DEATH) ~ as.factor(BOOZE_q) + AGEYRS, data = d)

# Age-adjusted Poisson model
poisson_age <- glm(DEATH ~ as.factor(BOOZE_q) + AGEYRS,
                   family = poisson(link = "log"),
                   offset = log(FU), data = d_pois)

# View results
summary(cox_age)
## Call:
## coxph(formula = Surv(FU, DEATH) ~ as.factor(BOOZE_q) + AGEYRS, 
##     data = d)
## 
##   n= 9250, number of events= 2145 
## 
##                                   coef exp(coef)  se(coef)      z Pr(>|z|)    
## as.factor(BOOZE_q)0–0.5/week  0.014101  1.014201  0.075143  0.188   0.8511    
## as.factor(BOOZE_q)0.5–2/week -0.037072  0.963606  0.063688 -0.582   0.5605    
## as.factor(BOOZE_q)>2/week     0.130416  1.139303  0.053551  2.435   0.0149 *  
## AGEYRS                        0.088717  1.092771  0.002572 34.492   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
##                              exp(coef) exp(-coef) lower .95 upper .95
## as.factor(BOOZE_q)0–0.5/week    1.0142     0.9860    0.8753     1.175
## as.factor(BOOZE_q)0.5–2/week    0.9636     1.0378    0.8505     1.092
## as.factor(BOOZE_q)>2/week       1.1393     0.8777    1.0258     1.265
## AGEYRS                          1.0928     0.9151    1.0873     1.098
## 
## Concordance= 0.751  (se = 0.005 )
## Likelihood ratio test= 1789  on 4 df,   p=<2e-16
## Wald test            = 1211  on 4 df,   p=<2e-16
## Score (logrank) test = 1496  on 4 df,   p=<2e-16
summary(poisson_age)
## 
## Call:
## glm(formula = DEATH ~ as.factor(BOOZE_q) + AGEYRS, family = poisson(link = "log"), 
##     data = d_pois, offset = log(FU))
## 
## Coefficients:
##                               Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                  -9.192240   0.169248 -54.312   <2e-16 ***
## as.factor(BOOZE_q)0–0.5/week  0.008057   0.075291   0.107   0.9148    
## as.factor(BOOZE_q)0.5–2/week -0.035776   0.063783  -0.561   0.5749    
## as.factor(BOOZE_q)>2/week     0.125441   0.053535   2.343   0.0191 *  
## AGEYRS                        0.086236   0.002549  33.837   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for poisson family taken to be 1)
## 
##     Null deviance: 9335.0  on 9245  degrees of freedom
## Residual deviance: 7625.5  on 9241  degrees of freedom
## AIC: 11918
## 
## Number of Fisher Scoring iterations: 6
# Tidy model outputs
cox_age_tidy     <- tidy(cox_age, exponentiate = TRUE, conf.int = TRUE)
cox_full_tidy    <- tidy(cox, exponentiate = TRUE, conf.int = TRUE)
poisson_age_tidy <- tidy(poisson_age, exponentiate = TRUE, conf.int = TRUE)
poisson_full_tidy<- tidy(poisson, exponentiate = TRUE, conf.int = TRUE)

booze_terms <- function(df, model_name) {
  df %>%
    filter(grepl("BOOZE_q", term)) %>%
    mutate(model = model_name,
           estimate_CI = paste0(round(estimate, 2), " (",
                                round(conf.low, 2), ", ",
                                round(conf.high, 2), ")")) %>%
    select(term, model, estimate_CI)
}

results <- bind_rows(
  booze_terms(cox_age_tidy, "Cox Age-adjusted"),
  booze_terms(cox_full_tidy, "Cox Full-adjusted"),
  booze_terms(poisson_age_tidy, "Poisson Age-adjusted"),
  booze_terms(poisson_full_tidy, "Poisson Full-adjusted")
)

table2_clean <- results %>%
  pivot_wider(names_from = model, values_from = estimate_CI)
#Table 3
tidy(cox_men, exponentiate = TRUE, conf.int = TRUE)
## # A tibble: 20 × 7
##    term                estimate std.error statistic   p.value conf.low conf.high
##    <chr>                  <dbl>     <dbl>     <dbl>     <dbl>    <dbl>     <dbl>
##  1 as.factor(BOOZE_q)…    1.03    0.106       0.292 7.71e-  1    0.838     1.27 
##  2 as.factor(BOOZE_q)…    0.856   0.0840     -1.84  6.51e-  2    0.726     1.01 
##  3 as.factor(BOOZE_q)…    0.885   0.0702     -1.74  8.23e-  2    0.771     1.02 
##  4 AGEYRS                 1.10    0.00359    26.3   4.31e-152    1.09      1.11 
##  5 as.factor(RACE)2       0.883   0.0991     -1.26  2.09e-  1    0.727     1.07 
##  6 as.factor(RACE)3       0.578   0.263      -2.08  3.72e-  2    0.346     0.968
##  7 as.factor(EDUC_CAT…    1.04    0.0803      0.523 6.01e-  1    0.891     1.22 
##  8 as.factor(EDUC_CAT…    0.935   0.0767     -0.872 3.83e-  1    0.805     1.09 
##  9 as.factor(EDUC_CAT…    0.833   0.108      -1.70  8.91e-  2    0.674     1.03 
## 10 as.factor(EDUC_CAT…    0.648   0.116      -3.74  1.88e-  4    0.517     0.814
## 11 as.factor(MARRY)3      1.14    0.113       1.15  2.51e-  1    0.913     1.42 
## 12 as.factor(MARRY)4      1.48    0.131       2.98  2.85e-  3    1.14      1.91 
## 13 as.factor(MARRY)5      1.39    0.184       1.79  7.30e-  2    0.970     2.00 
## 14 as.factor(MARRY)6      1.41    0.126       2.72  6.58e-  3    1.10      1.80 
## 15 as.factor(MARRY)8      1.62    0.453       1.07  2.85e-  1    0.668     3.94 
## 16 BMI                    0.982   0.00729    -2.54  1.09e-  2    0.968     0.996
## 17 AVGSMK                 1.02    0.00187    10.4   2.20e- 25    1.02      1.02 
## 18 as.factor(SIZE_CAT…    1.05    0.0929      0.534 5.93e-  1    0.876     1.26 
## 19 as.factor(SIZE_CAT…    1.12    0.0966      1.13  2.58e-  1    0.923     1.35 
## 20 as.factor(SIZE_CAT…    0.968   0.0704     -0.458 6.47e-  1    0.843     1.11
tidy(cox_women, exponentiate = TRUE, conf.int = TRUE)
## # A tibble: 20 × 7
##    term                estimate std.error statistic   p.value conf.low conf.high
##    <chr>                  <dbl>     <dbl>     <dbl>     <dbl>    <dbl>     <dbl>
##  1 as.factor(BOOZE_q)…    0.967   0.109     -0.307  7.59e-  1    0.781      1.20
##  2 as.factor(BOOZE_q)…    0.841   0.105     -1.65   9.84e-  2    0.684      1.03
##  3 as.factor(BOOZE_q)…    0.949   0.107     -0.487  6.26e-  1    0.770      1.17
##  4 AGEYRS                 1.10    0.00446   21.3    8.20e-101    1.09       1.11
##  5 as.factor(RACE)2       1.06    0.118      0.493  6.22e-  1    0.841      1.34
##  6 as.factor(RACE)3       0.987   0.307     -0.0423 9.66e-  1    0.541      1.80
##  7 as.factor(EDUC_CAT…    0.960   0.0987    -0.414  6.79e-  1    0.791      1.16
##  8 as.factor(EDUC_CAT…    0.968   0.0886    -0.367  7.13e-  1    0.814      1.15
##  9 as.factor(EDUC_CAT…    0.830   0.131     -1.42   1.55e-  1    0.642      1.07
## 10 as.factor(EDUC_CAT…    0.932   0.139     -0.511  6.10e-  1    0.710      1.22
## 11 as.factor(MARRY)3      1.07    0.0780     0.812  4.17e-  1    0.914      1.24
## 12 as.factor(MARRY)4      0.858   0.163     -0.942  3.46e-  1    0.624      1.18
## 13 as.factor(MARRY)5      1.26    0.238      0.983  3.26e-  1    0.792      2.02
## 14 as.factor(MARRY)6      0.980   0.156     -0.130  8.96e-  1    0.722      1.33
## 15 as.factor(MARRY)8      0.994   0.505     -0.0114 9.91e-  1    0.369      2.68
## 16 BMI                    1.00    0.00642   -0.0406 9.68e-  1    0.987      1.01
## 17 AVGSMK                 1.03    0.00267    9.88   4.87e- 23    1.02       1.03
## 18 as.factor(SIZE_CAT…    1.03    0.105      0.267  7.90e-  1    0.837      1.26
## 19 as.factor(SIZE_CAT…    0.910   0.110     -0.859  3.90e-  1    0.734      1.13
## 20 as.factor(SIZE_CAT…    0.986   0.0850    -0.168  8.67e-  1    0.835      1.16
tidy(cox_product)
## # A tibble: 24 × 5
##    term                            estimate std.error statistic   p.value
##    <chr>                              <dbl>     <dbl>     <dbl>     <dbl>
##  1 as.factor(BOOZE_q)0–0.5/week     0.0786    0.236      0.332  7.40e-  1
##  2 as.factor(BOOZE_q)0.5–2/week    -0.181     0.194     -0.934  3.50e-  1
##  3 as.factor(BOOZE_q)>2/week       -0.236     0.167     -1.42   1.56e-  1
##  4 SEX                             -0.652     0.0648   -10.1    8.98e- 24
##  5 AGEYRS                           0.0947    0.00278   34.1    6.05e-255
##  6 as.factor(RACE)2                -0.0432    0.0754    -0.573  5.67e-  1
##  7 as.factor(RACE)3                -0.344     0.199     -1.73   8.42e-  2
##  8 as.factor(EDUC_CAT)Some HS       0.00447   0.0622     0.0718 9.43e-  1
##  9 as.factor(EDUC_CAT)HS Grad      -0.0619    0.0577    -1.07   2.84e-  1
## 10 as.factor(EDUC_CAT)Some College -0.206     0.0829    -2.48   1.30e-  2
## # ℹ 14 more rows